N BE Computer Science and Engineering internet of Things and Cyber Security Including Block Chain Technology Sem VII VIII_1 Syllabus Mumbai University

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AC – 01/11/2023
Item No. – 6.6 (N)





University of Mumbai








Syllabus for
B.E. ( Computer Science and Engineering)
(Internet of Things and Cyber Security
including Block chain Technology)

Semester – VII & VIII

Choice Based Credit System
REV- 2019 ‘C’ Scheme

(With effect from the academic year 202 3-24)

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University of Mumbai












Dr. Deven Shah Dr. Shivram Garje
Offg. Associate Dean Offg. Dean
Faculty of Science and Technology Faculty of Science and Technology
Sr. No. Heading Particulars
1 Title of Course
B.E. (Computer Science and
Engineering) (Internet of Things and
Cyber Security including Block chain
Technology)
2 Eligibility

After Passing Third Year Engineering
as per the Ordinance 0.6243
3 Passing Marks
40%

4 Ordinances /
Regulations (if any) Ordinance 0.6243
5 No. of Years / Semesters 4 Years/ 8 semesters
6 Level Under Graduation

7 Pattern Semester

8 Status New
REV-2019 ‘C’ Scheme

9 To be implemented from
Academic Year
With effect from the academic year
2023 -24

Syllabus for Approval

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Preamble

To meet the challenge of ensuring excellence in engineering education, the issue of quality needs to be
addressed, debated and taken forward in a systematic manner. Accreditation is the principal means of
quality assurance in higher education. The major em phasis of accreditation process is to measure the
outcomes of the program that is being accredited. In line with this Faculty of Science and Technology (in
particular Engineering) of University of Mumbai has taken a lead in incorporating philosophy of outc ome
based education in the process of curriculum development.
Faculty resolved that course objectives and course outcomes are to be clearly defined for each course, so
that all faculty members in affiliated institutes understand the depth and approach of c ourse to be taught,
which will enhance learner’s learning process. Choice based Credit and grading system enables a much -
required shift in focus from teacher -centric to learner -centric education since the workload estimated is
based on the investment of time in learning and not in teaching. It also focuses on continuous evaluation
which will enhance the qualit y of education. Credit assignment for courses is based on 15 weeks teaching
learning process, however content of courses is to be taught in 13 weeks and remaining 2 weeks to be
utilized for revision, guest lectures, coverage of content beyond syllabus etc.
There was a concern that the earlier revised curriculum more focused on providing information and
knowledge across various domains of the said program, which led to heavily loading of students in terms
of direct contact hours. In this regard, faculty of s cience and technology resolved that to minimize the
burden of contact hours, total credits of entire program will be of 170, wherein focus is not only on
providing knowledge but also on building skills, attitude and self learning. Therefore in the present
curriculum skill based laboratories and mini projects are made mandatory across all disciplines of
engineering in second and third year of programs, which will definitely facilitate self learning of students.
The overall credits and approach of curriculum proposed in the present revision is in line with AICTE
model curriculum.
The present curriculum will be implemented for Second Year of Engineering from the academic year 2021 -
22. Subsequently this will be carried forward for Third Year and Final Year Engin eering in the academic
years 2022 -23, 2023 -24, respectively.

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Incorporation and Implementation of Online Contents
from NPTEL/ Swayam Platform



The curriculum revision is mainly focused on knowledge component, skill based activities
and project based activities. Self-learning opportunities are provided to learners. In the revision
process this time in particular Revised syllabus of ‘C’ scheme wher ever possible additional
resource links of platforms such as NPTEL, Swayam are appropriately provided. In an earlier
revision of curriculum in the year 2012 and 2016 in Revised scheme ‘A' and ‘B' respectively,
efforts were made to use online contents more appropriately as additional learning materials
to enhance learning of students.
In the current revision based on the recommendation of AICTE model curriculum overall
credits are reduced to 171, to provide opportunity of self -learning to learner. Learners a re
now getting sufficient time for self -learning either through online courses or additional
projects for enhancing their knowledge and skill sets.
The Principals/ HoD’s/ Faculties of all the institute are required to motivate and encourage
learners to use additional online resources available on platforms such as NPTEL/ Swayam.
Learners can be advised to take up online courses, on successful completion they are required
to submit certification for the same. This will definitely help learners to facilitate their
enhanced learning based on their interest.

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Preface by Board of Studies Team

It is our honor and a privilege to present the Rev -2019 ‘C’ scheme syllabus of the Bachelor of Computer Science and
Engineering in the (Internet of Thing and Cyber Security including Blockchain) (effective from the year 20 21-22).
AICTE has introduced Computer Science and Engineering in the (Internet of Thing and Cyber Security including
Blockchain) as one of the nine emerging technology and hence many colleges affiliated with the University of Mumbai
has started four years UG program for Computer Science and Engineering in the (Internet of Thing and Cyber Security
including Blockchain). As part of the policy decision from the University end, the Board of IT got an opportunity to
work on designing the syllabus for this new br anch. As the Computer Science and Engineering in the (Internet of Thing
and Cyber Security including Blockchain)is comparatively a young branch among other emerging engineering
disciplines in the University of Mumbai, and hence while designing the syllabus promotion of an
interdisciplinary approach has been considered.

The branch also provides multi -faceted scope like better placement and promotion of entrepreneurship culture among
students and increased Industry Institute Interactions. Industries' views a re considered as stakeholders while the
design of the syllabus. As per Industry views only 16 % of graduates are directly employable. One of the reasons is a
syllabus that is not in line with the latest emerging technologies. Our team of faculties has trie d to include all the latest
emerging technologies in the Computer Science and Engineering in the (Internet of Thing and Cyber Security including
Blockchain) syllabus. Also the first time we are giving skill -based labs and Mini -project to students from the third
semester onwards, which will help students to work on the latest Computer Science and Engineering in the (Internet of
Thing and Cyber Security including Blockchain) technologies. Also the first time we are giving the choice of elective
from fifth sem ester such that students will be mastered in one of the Internet of Thing domain. The syllabus is peer -
reviewed by experts from reputed industries and as per their suggestions, it covers future emerging trends in Computer
Science and Engineering in the (In ternet of Thing and Cyber Security including Blockchain) technology and research
opportunities available due to these trends. .

We would like to thank senior faculties of IT, Computer and Electronics Department, of all colleges affiliated to
University of Mumbai for significant contribution in framing the syllabus. Also on behalf of all faculties we thank all
the industry experts for their valuable feedback and suggestions. We sincerely hope that the revised syllabus will help
all graduate engineers to fac e the future challenges in the field of Emerging Areas of Computer Science and
Engineering in the (Internet of Thing and Cyber Security including Blockchain).

Program Specific Outcome for graduate Program in Computer Science and Engineering (Internet of T hing and
Cyber Security including Blockchain)

1. Apply Core of IoT, Cyber Security & Blockchain knowledge to develop stable and secure
Application.
2. Identify the issues of IoT, Cyber Security including Blockchain in real time application and in all three area of
domain.
3. Ability to apply and develop IoT & Cyber Security including Blockchain multidisciplinary projects.

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Program Structure for Fourth Year Engineering
Semester VII & VIII
UNIVERSITY OF MUMBAI
(With Effect from 2023 -24)
Semester VII

Course Code
Course Name Teaching scheme
(Contact Hours)
Credits Assigned
Theory Pract Theory Pract Total
IoTCSBCC701 Machine Learning &
Blockchain 3 -- 3 -- 3
IoTCSBCC702 Edge / Fog Computing 3 -- 3 3
IoTCSBCDO701
X Department Optional
Course – 3 3 -- 3 -- 3
IoTCSBCDO702
X Department Optional
Course –4 3 -- 3 -- 3
IoTCSBCIO701X Institute Optional
Course – 1 3 -- 3 -- 3
IoTCSBCL701 ML & BC Lab -- 2 -
- 1 1
IoTCSBCL702 Edge / Fog Computing
Lab -- 2 -
- 1 1
IoTCSBCL703 DevSecOps Lab -- 2 -
- 1 1
IoTCSBCL704 Open -Source
Intelligence (OSINT)
Lab -- 2 -
- 1 1
IoTCSBCP701 Major Project I -- 6# -
- 3 3
Total 15 14 15 7 22

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Course Code


Course Name Examination Scheme
Theory Term
Work Prac t Tota l

Internal
Assessment End
Sem
Exam Exam.
Duration
(in Hrs)
Test1 Test2 Avg
IoTCSBCC701 Machine Learning &
Blockchain 20 20 20 80 3 -- -- 100
IoTCSBCC702 Edge / Fog Computing 20 20 20 80 3 -- -- 100
IoTCSBCDO701
X Department
Optional Course – 3 20 20 20 80 3 -- -- 100
IoTCSBCDO702
X Department
Optional Course –
4 20 20 20 80 3 -- -- 100
IoTCSBCIO701X Institute Optional
Course – 1 20 20 20 80 3 -- -- 100
IoTCSBCL701 ML & BC Lab -- -- -- -- -- 25 25 50
IoTCSBCL702 Edge / Fog Computing
Lab -- -- -- -- -- 25 25 50
IoTCSBCL703 DevSecOps Lab -- -- -- -- -- 25 25 50
IoTCSBCL704 Open -Source
Intelligence (OSINT)
Lab -- -- -- -- -- 25 25 50
IoTCSBCP701 Major Project I -- -- -- -- -- 25 25 50
Total -- -- 100 400 -- 125 125 750
# indicates work load of Learner (Not Faculty), for Major Project
IoTCSBCDO701X Department Optional Course –3
IoTCSBCDO701 1 Advance Cloud Computing Security
IoTCSBCDO701 2 Software Testing & Quality Assurance (STQA)
IoTCSBCDO701 3 IoT for Smart Cities
IoTCSBCDO701 4 Supervisory Control and Data acquisition (SCADA) Security

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IoTCSBCDO702X Department Optional Course –4
IoTCSBCDO702 1 DESIGN A BLOCKCHAIN APPLICATION ARCHITECTURE
IoTCSBCDO702 2 Usability & Security in UID
IoTCSBCDO702 3 Enterprise IoT Cyber Security
IoTCSBCDO702 4 Software Engineering & Testing Methodology for IoT



# Institute Level Optional Course (ILO)

Every student is required to take one Institute Elective Course for Semester VII, which is
not closely allied to their disciplines. Different sets of courses will run in the both the semesters.

















ILO701X Institute Optional Course – 1 ( Common for all branches will be notified )
ILO7011 Product Lifecycle Management
ILO7012 Reliability Engineering
ILO7013 Management Information System
ILO7014 Design of Experiments
ILO7015 Operation Research
ILO7016 Cyber Security and Laws
ILO7017 Disaster Management and Mitigation
Measures
ILO7018 Energy Audit and Management
ILO7019 Development Engineering

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Program Structure for Fourth Year Engineering Semester VII & VIII
UNIVERSITY OFMUMBAI
(With Effect from 2023 -24)

Semester VIII


Course
Code
Course Name Teaching Scheme (Contact
Hours)
Credits Assigned
Theory Pract.
Tut. Theory Pract. Total
IoTCSBCC
801 NFT & DeFi (Decentralized
Finance) 3 -- 3 -- 3
IoTCSBC D
O801X Department Optional Course – 5 3 -- 3 -- 3
IoTCSBC D
O802X Department Optional Course – 6 3 -- 3 -- 3
IoTCSBC I
O801X Institute Optional Course – 2
3 -- 3 -- 3
IoTCSBCL
801 Capstone Lab -- 2 -- 1 1
IoTCSBCL
802 IoT Automation Lab -- 2 -- 1 1
IoTCSBCP
801 Major Project II
-- 12# -- 6 6
Total 12 16 12 8 20



Course
Code



Course Name Examination Scheme
Theory Term
Work Prac
/oral Total

Internal Assessment End
Sem
Exam Exam.
Duratio n
(in Hrs)
Test1 Test2 Avg
IoTCSBCC
801 NFT & DeFi (Decentralized
Finance) 20 20 20 80 3 -- -- 100
IoTCSBC D
O801X Department Optional Course – 5 20 20 20 80 3 -- -- 100
IoTCSBC D
O802X Department Optional Course – 6 20 20 20 80 3 -- -- 100
IoTCSBC I
O801X Institute Optional Course – 2
20 20 20 80 3 -- -- 100
IoTCSBCL
801 Capstone Lab -- -- -- -- -- 25 25 50
IoTCSBCL
802 IoT Automation Lab -- -- -- -- -- 25 25 50
IoTCSBCP Major Project II
-- -- -- -- -- 100 50 150

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801
Total -- -- 80 320 -- 150 100 650
# indicates work load of Learner (Not Faculty), for Major Project

Students group and load of faculty per week.

Mini Project 1 and 2 :
Students can form groups with minimum 2 (Two) and not more than 4 (Four)
Faculty Load : 1 hour per week per four groups



Major Project 1 and 2 :
Students can form groups with minimum 2 (Two) and not more than 4 (Four)
Faculty Load : In Semester VII – ½ hour per week per project group
In Semester VIII – 1 hour per week per project group

IoTCSBCDO801X Department Optional Course – 5
IoTCSBCDO8011 Emerging Applications of Blockchain in industry
IoTCSBCDO8012 IoTs & Embedded Security
IoTCSBCDO8013 Information Retrieval System
IoTCSBCDO8014 Intelligent Forensic


IoTCSBC DO802X Department Optional Course –6
IoTCSBCDO8 021 IoT for Smart Grids
IoTCSBCDO8 022 Metaverse
IoTCSBCDO8 023 Green IT
IoTCSBCDO8 024 Cyber Security laws & legal accepts

# Institute Level Optional Course (ILO)

Every student is required to take one Institute Elective Course for Semester VI II, which is
not closely allied to their disciplines. Different sets of courses will run in the both
the semesters.
ILO801X Institute Optional Course – 2 ( Common for all branches will be notified )
ILO8011 Project Management
ILO8012 Finance Management
ILO8013 Entrepreneurship Development
and Management
ILO8014 Human Resource Management
ILO8015 Professional Ethics and CSR
ILO8016 Research Methodology
ILO8017 IPR and Patenting
ILO8018 Digital Business Management
ILO8019 Environmental Management

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Subject Code Subject Name Theory Practical Tutorial Theory Practical/Oral Tutorial Total
IoTCSBCC701 Machine
Learning &
Blockchain 03 -- -- 03 -- -- 03

Subject Code Subject Name Examination Scheme
Theory Marks
Term
Work Practica
l Ora
l Tota
l Internal Assessment End
Sem.
Exam Test1 Test 2 Avg. of
2 Tests
IoTCSBCC70
1 Machine
Learning &
Blockchain 20 20 20 80 -- -- -- 100

Course Objectives: Six Course Objectives

Sr. No. Course Objectives
The course aims:
1 To learn the basic terminologies used in machine learning and preprocessing of data.
2 To learn Feature Selection and various algorithms
3 To learn concepts of Neural Network and Deep Learning
4 To learn key concepts and basics of Blockchain
5 To learn the Consensus mechanism and Smart contracts
6 To learn application areas of Blockchain

Course Outcomes: Six Course Outcomes (Based on Bloom's Taxonomy)

Sr.
No. Course Outcomes Cognitive levels of
attainment as per
Bloom’s Taxonomy
On successful completion, of course, learner/student will be able to:
1 Understand Machine learning, Neural & Deep Learning Concepts. L2
2 Evaluate mathematical parameters and regression concepts towards building
efficient models. L3
3 Discuss architectural paradigms with respect to Neural networks and deep learning. L2
4 Understand the fundamentals of emerging blockchain technology. L2
5 Evaluate the different consensus algorithms, and smart contracts while developing
solutions. L5
6 Delineate the New areas of applications for blockchain and machine learning. L6

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Prerequisite: Introduction to Cryptography , Basic Mathematics & Statistics
DETAILED SYLLABUS:
Sr.
No. Module Detailed Content Hours CO
Mapping
0 Prerequisite 1. Mathematics: Vectors, matrices, matrix operations,
eigenvalues, eigenvectors, Differentiation, integration,
Probability theory
2. Statistics: Descriptive statistics, Inferential statistics,
Probability distributions 2 --
I Introduction to
Machine Learning Introduction: -
Introduction: - What Is Learning? When Do We Need Machine
Learning?
Types of Learning, Relations to Other Fields

Basic Terminology & Framework: - Machine Learning
Terminology
Roadmap for building machine learning -- Preprocessing,
Training, and Model selection, Evaluating and Predicting
Python for machine learning -- Packages for scientific
computing, data science, and machine learning

Data Preprocessing: -
Dealing with missing data, Handling Categorical data,
Partitioning a dataset into separate training and te st datasets,
Bringing features onto the same scale, Select meaningful
features

Self-learning Topics: Installation and Configuration of
development environment for machine Learning. 7 CO1
II Feature Selection &
Algorithms Feature Selection: - Feature Selection & Filtering, Principal
Component Analysis

Algorithms: -
Regression: - Ridge, Lasso, ElasticNet, Polynomial, Isotonic,
Logistic.
Naive Bayes: - Bayes' Theorem, Naive Bayes Classifier,
Bernoulli Naive Bayes, Multinomial Naive Bayes, Gaussian
Naive B ayes
Decision Tree & Ensemble Learning: - Binary decision tree,
Random Forest, AdaBoost, Gradient Tree Boost.
Clustering: - K-Means Clustering

Self-learning Topics: Compare the different algorithms for
accuracy, precision, recall, F1 -score, etc 9 CO2
III Introduction to
Neural Network and
Deep Learning Introduction to Neural Network: -- Basic Architecture of
Neural Networks for Perceptron and Multi -Layer Neural
Network, Training Neural Network with Backpropagation,
Issues in Neural Network Training

Introduction to Deep Learning: -- Artificial neural Network,
Deep architecture, Brief introduction to Tensor Flow

Self-learning Topics: Training Deep Neural Networks and 7 CO3

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Issues
IV Introduction to
Blockchain Introduction: -- History of Blockchain, What is Blockchain?,
Centralized v/s Decentralized System, Layers of Blockchain,
Advantage of Blockchain

Blockchain Foundation: - Cryptography -- Symmetric,
Asymmetric, Hash function, Game Theory -- Nash
Equilibrium, Prisoner's Dile mma, Byzantine Generals'
Problem, Zero -Sum Games, Trees - Merkle Trees

Self-learning Topics: Explore the data structure used in
blockchain and study Information retrieval. 8 CO4
V Consensus
Mechanism & Smart
Contract
Consensus Mechanism: - Introduction to consensus protocols,
Types of Consensus algorithm (PoW, PoS, PoET), Key privacy
challenges of the blockchain

Smart Contracts: Introduction to Smart Contracts, Working
of Smart Contracts, Decentralized Applications, Challenges in
Decentralized Applicat ions.

Self-learning Topics : Explore and Compare various
blockchain platforms 6 CO5
VI Application of
Blockchain Blockchain Applications: - Cryptocurrency, Blockchain in
Health Care

Self-Learning Topics: Research papers referred in Online
Reference No. 6 & 7
3 CO6

Text Books:
1. Shai Shalev -Shwartz; Shai Ben -David, MACHINE LEARNING From Theory to Algorithms,
Cambridge University Press, 2014
2. Sebastian Raschka; Yuxi (Hayden) Liu, Vahid Mirjalili , Machine Learning with PyTorch and Scikit -
Learn, PackT, 2022
3. Giuseppe Bonaccorso, Machine Learning Algorithm, Packt, 2017
4. Charu C Aggarwal, Neural Network & Deep Learning A Textbook, Springer, 2018
5. Bikramaditya Singhal, Gautam Dhameja, Priyansu Sekhar Pan da, Beginning Blockchain A Beginner's
Guide to Building Blockchain Solutions, Apress, 2018
6. Kirankalyan Kulkarni, Learn Bitcoin and Blockchain, Packt, 2018
7. Sandeep Kumar Panda, Vaibhav Mishra, Sujata Priyambada Dash, Ashis Kumar Pani, Recent Advances
in Blo ckchain Technology Real -World Applications, Springer, 2023

References:
1. Vinod Chandra S.S, Anand Hareendran S, Machine Learning A practitioner's Approach, PHI, 2021
2. Gaur, Nitin, et al. Blockchain with hyperledger fabric: Build decentralized applications using
hyperledger fabric 2 . Packt Publishing Ltd, 2020.
3. Mastering Bitcoin: Unlocking Digital Cryptocurrencies, by Andreas Antonopoulos

Online References:
1. Live Demo : https://andersbrownworth.com/blockchain/
2. Udemy Course - Machine Learning & Deep Learning in Python & R –
https://www.udemy.com/course/data_science_a_to_z/
3. Public github repository with code samples:

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https://github.com/HyperledgerHandsOn/trade -finance -logistics
4. Hyperledger Fabric - https://www.hyperledger.org/projects/fabric
5. NPTEL – Introduction to Machine Learning - https://nptel.ac.in/courses/106106139
6. Shah, D., Patel, D., Adesara, J. et al. Exploiting the Capabilities of Blockchain and Machine Learning in
Education. Augment Hum Res 6, 1 (2021). https://doi.org/10.1007/s41133 -020-00039 -7
7. M. Hassan, J. Chen, C. Zhu and U. Zukaib, "Adoption of Blockchain -based Artificial Intelligence in
Healthcare," 2022 5th Interna tional Conference on Artificial Intelligence and Big Data (ICAIBD) , Chengdu, China,
2022, pp. 140 -144, doi: 10.1109/ICAIBD55127.2022.9820137.


Assessment:
Internal Assessment (IA) for 20 marks:
● IA will consist of Two Compulsory Internal Assessment Tests. Approximately 40% to 50% of syllabus
content must be covered in First IA Test and remaining 40% to 50% of syllabus content must be covered in
Second IA Test
Question paper format
● Question Paper will comprise of a total of six questions each carrying 20 marks Q.1 will be compulsory
and should cover maximum contents of the syllabus.
● Remaining questions will be mixed in nature (part (a) and part (b) of each question must be from different
modules. For example, if Q.2 has part (a) from Module 3 then part (b) must be from any other Module
randomly selected from all the modules)
● A total of four questions needs to be answered.

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Course Code Course Name Theory Practical Tutorial Theory Oral Tutorial Total
IoTCSBC702 Edge and Fog
Computing
03 -- -- 03 -- -- 03

Course Code Course Name Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End
Sem.
Exam Test1 Test 2 Avg. of
2 Tests
IoTCSBC702 Edge and Fog
Computing
20 20 20 80 -- -- -- 100

Course Objectives:

Sr. No. Course Objectives:
The course aims:
1 Understand the fundamentals of edge computing and its role in IoT systems.
2 Analyze and compare different edge computing architectures , platforms and frameworks.
3 Analyze and evaluate data processing at the edge and Edge analytics .
4 Understand the fundamentals of fog computing and its frameworks .
5 Demonstrate effective communication and collaboration skills in developing edge
computing projects.

Course Outcomes:
Sr. No. Course Outcomes Cognitive levels of
attainment as per
Bloom’s Taxonomy
On successful completion, of course, learner/student will be able to:
1 Understand the basic concepts of Edge Computing and its collaboration
with Cloud Computing . L2
2 Understand and i dentify edge computing architecture and various
platforms and frameworks and Demonstrate knowledge of virtualization
and containerization L3
3 To apply data processing capabilities along with edge analytics and
caching to process and extract insights from data at the edge L3

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4 To understand the fundamentals of Fog computing and its architecture . L3
5 To develop programming for fog computing -based applications and
framework s. L4
6 To develop edge computing solutions for specific IoT use cases or
scenarios. L6

Prerequisite: Linear algebra, Probability theory and Basic statistics
Sr.
No. Module Detailed Content Hours CO
Mapping
0 Prerequisite Basic concepts of Cloud Computing and virtualization 2 --
I Introduction to
Edge Computing
and IoT Understanding Edge Computing: Evolution, Use cases,
advantages, disadvantages, Overview of edge computing
and its significance in IoT , Challenges and opportunities
in edge computing .
Self-Learning Topics: Edge devices and their
capabilities 07 CO1
II Edge Computing
Infrastructure
Edge computing architectures and components:
Requirements and views for Edge architecture, Edge
Computing Reference Architecture, critical elements for
Edge architecture, Challenges for Edge application
Development. Setti ng up Edge computing environments:
development tools, python libraries.
Edge computing platforms and frameworks: AWS IoT
Greengrass, Azure IoT Edge, Google Cloud IoT Edge,
IBM Edge Application Manager, KubeEdge.
Virtualization and containerization for edge computing:
Introduction to Virtualization and containerization.
Advantages of Virtualization and Containerization in
Edge Computing. Resource Efficiency, Faster Time to
Market.
Self-Learning Topics: Apache Edgent, Eclipse ioFog. 09 CO2
III Data Processing
at the Edge
Data Acquisition and P rocessing: Data handling, python
data handling, data storage and cloud connectivity , Data
Aggregation, Data Timestamping and Synchronization,
Data Security and Privacy.
Edge analytics and machine learning at the edge:
Introduction to Edge Analytics. Edge Machine Learning.
Model Selection and Optimization. Collaborative Edge
Learning.
Resource management and task offloading strategies:
Task Offloading, Edge -Cloud Collabor ation, Dynamic
Resource Provisioning.
Edge caching and data synchronization: Introduction to
Edge caching and data synchronization, Benefits of Edge
Caching and Data Synchronization, Challenges in Edge 07 CO3

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Caching and Data Synchronization.
Self-Learning Topi cs: Task Migration, Offline
Operation, Bandwidth Optimization .

IV Introduction to
Fog Computing Definition and basic concepts, Comparison with cloud
computing and IoT, Data Management in Fog
Computing. Comparison with cloud computing and
edge computing.
Fog Computing Architecture. Fog node and
infrastructure components. Hierarchical and distributed
models. Programming Models and Tools for Fog
Computing
Self-Learning Topics: Applications and integration
of Fog Computing. 06 CO4
V Fog computing
programming
languages and
frameworks Middleware and software platforms. Development and
deployment considerations. Industrial Internet of Things
(IIoT). Performance Evaluation and Metrics in Fog
Computing. Simulation and modelling techniques.
Applications and Use Cases of Fog Computing
Self-Learning Topics: Development environments
and Frameworks for programming in Fog
Computing. 06 CO5
VI Applications and
Case Studies High -Potential Use cases, Edge computing for smart
cities. Industrial IoT and edge computing. Edge
computing in Healthcare.
03 CO6


Text Books:
1. “Fog and Edge Computing ” by Rajkumar Buyya, Satish Narayana Srirama, Wiley Publications
2. "Edge Computing: Models, Technologies, and Applications" by Mung Chiang, Bharath
Balasubramanian, and H. Vincent Poor.
3. Edge Computing with Python: End -to-end Edge Applications, Python Tools and Techniques, Edge
Architectures, and AI Benefit” by Abhinandan Bhadauria, BPB publications .
4. “Edge Computin g: Simply in Depth” by Ajit Singh,
5. Edge Computing: Fundamentals, Advances and Applications (Advances in Industry 4.0 and
Machine Learning) by K. Anitha Kumari, G. Sudha Sadasivam, D. Dharani, M. Niranjanamurthy ,
CRC Press.


References:

1. "Edge Computing for IoT: Architectures and Applications" by Bharat Bhargava, Sudip Misra,
Valentina E. Balas, and Raghvendra Kumar
2. "Practical Industrial Internet of Things Security: A practitioner's guide to securing connected
industries" by Sravani Bhatta charjee and Rajdeep Chowdhury
3. "Edge Computing: An Introduction to the Next Generation of Networked Systems" by Kiran
Chitturi, Bharadwaj Veeravalli, and Satish Narayana Srirama
4. "Building the Web of Things: With examples in Node.js and Raspberry Pi" by Domi nique D.
Guinard and Vlad M. Trifa

Page 20

5. "Internet of Things (IoT): Technologies, Applications, Challenges, and Solutions" edited by
Balamuralidhar P., Bharadwaj Veeravalli, and V. Raghu
6. "Fog and Edge Computing: Principles and Paradigms" by Rajkumar Buyya, Satis h Srirama, and
Pradeep Kumar S.
7. "IoT Fundamentals: Networking Technologies, Protocols, and Use Cases for the Internet of Things"
by David Hanes and Gonzalo Salgueiro
8. "Edge Analytics in IoT" by Shivashankar B. Nair, Siddhartha Bhattacharyya, and Thomas Edwa rd
Joshua
9. "Edge Computing: The Convergence of Big Data and Internet of Things" by Samee U. Khan, Albert
Y. Zomaya, and Salman A. Baset


Online References:
1. Wearables -a-new-opportunity -in-banking – Cisco
2. https://codereality.net/wearable -computing/
3. Mohd Javaid, Abid Haleem, Ravi Pratap Singh, Shanay Rab, Rajiv Suman,Internet of
Behaviors (IoB) and its role in customer services, Sensors International,Volume 2, 2021,
100122, ISSN 2666 -3511, https://doi.org/10.1016/j.sintl.2021.100122
MOOC Courses:
1. https://w ww.mooc -list.com/tags/wearable -technology
Assessment:
Internal Assessment (IA) for 20 marks:
● IA will consist of Two Compulsory Internal Assessment Tests. Approximately 40% to 50% of syllabus content
must be covered in First IA Test and remaining 40% to 50% of syllabus content must be covered in Second IA
Test
Question paper format
● Question Paper will comprise of a total of six questions each carrying 20 marks. Q.1 will be compulsory and
should cover maximum contents of the syllabus.
● Remaining questions will be mixed in nature (part (a) and part (b) of each question must be from different
modules. For example, if Q.2 has part (a) from Module 3 then part (b) must be from any other Module randomly
selected from all the modules)
● A total of four q uestions needs to be answered.

Page 21

Course Code Course Name Theory Practical Tutorial Theory Oral Tutorial Total
IoTCSBC DO
7011 Advanced Cloud
Computing
Security 03 -- -- 03 -- -- 03

Course
Code Course Name Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End Sem.
Exam Test1 Test
2 Avg. of 2
Tests
IoTCSBC D
O701 1 Advanced Cloud
Computing
Security 20 20 20 80 -- -- -- 100

Course Objectives:
Sr. No. Course Objectives
The course aims:
1 To understand the concept of security and its significance in the context of cloud computing.
2 To study cloud infrastructure security and mitigation techniques
3 To understand the working of Data center and Data Protection techniques
4 To develop a comprehensive understanding of challenges and solutions in secure identity management for
cloud environments
5 To study Compliance and Security Audits policies for cloud data
6 To understand the Cloud Native Security

Course Outcomes:
Sr. No. Course Outcomes Cognitive levels of
attainment as per
Bloom’s Taxonomy
On successful completion, of course, learner/student will be able to:
1 Understand the concept of security and its importance in the context of
cloud computing. L2
2 Analyze cloud infrastructure security and apply different mitigation
techniques. L3, L4
3 Apply different data protection techniques in data centers. L3
4 Design and implement secure identity management solutions for cloud
environments L6
5 Interpret and appropriately apply the policies on Compliance and Security
Audits for cloud data L2, L3
6 Demonstrate cloud security tools for designing, implementing, and
managing cloud -native security L2, L6

Prerequisite: Knowledge of Cloud Computing and Cryptography and Network Security
DETAILED SYLLABUS

Page 22

Sr.
No. Module Detailed Content Hours CO
Mapping
0 Prerequisite Basics of cloud computing, network and system security 2
I Fundamentals
Of Cloud
Security
Concepts


What is security, why is it required in cloud computing, Different types of
security in cloud, attacks, and vulnerabilities
Cloud Security Concepts - CIA Triad (Confidentiality, integri ty,
availability), privacy, authentication, non -repudiation, access control,
defence in depth, least privilege , Traditional vs Cloud Security,
importance, challenges in different cloud environment (public, private,
hybrid, muti -cloud)
Self-Learning Topic: Real-world Example of CIA Triad -
Bank ATM 5 CO1
II Cloud
Infrastructure
Security:
Threats and
Mitigation
Techniques Secure Infrastructure architecture
Infrastructure Security: Network Level, Host Level and Application
Level
Common attack vectors and threats
Mitigation techniques - Isolation, Virtualization and Segmentation,
Intruder Detection and prevention, Firewall, OS Hardening and
minimization, Verified and measured boot.
Self-Learning Topics: DoS, Man-in-the-Cloud, Insecure APIs, Insider
Threats, Cookie Poisoning, Cloud Malware Injection, 7 CO2
III Cloud Data
Security



Cloud security principles
Aspects of Data Security
Mitigation techniques : Data retention, deletion and archiving procedures
for tenant data, Encryption, Data Redaction, Tokenization, Obfuscation,
PKI and Key
Data center Security and Data Protection: Physical and network data
center security, Implementation of securit y in Virtual Data centers, East -
west Traffic Protections, Types of firewall, IDS and IPS, DMZ
Provider Data and Its Security
Self-Learning Topics:
Case studies: Capital One Data Breach, Uber's AWS Data Breach, Dow
Jones Data Leak, Accenture AWS S3 Data Ex posure, Verizon AWS S3
Data Exposure 6 CO3
IV Secure
Identity
Management
in The Cloud:
Challenges
And
Solutions IAM overview, Trust Boundaries and IAM, Architecture / Lifecycle
process, IAM standards and protocols, IAM Challenges
Cloud Authorization Management:
Identity management - User Identification, Authentication and
Authorization
Roles -based Access Control - Multi -factor authentication, Single Sign -
on, Identity Federation
Cloud Service Provider IAM Practice
Self-Learning Topic: IAM service in AWS 6 CO4
V Disaster
Recovery
Auditing:
Mitigating
Risk and
Ensuring
Compliance Cloud disaster recovery, types of disasters recovery, benefits of disaster
recovery, cloud disaster recovery planning
Privacy: Data life cycle, key privacy concerns in cloud, privacy risk
management and compliance, legal and regulatory implications,
Cloud Audit and Compliance: Internal Policy Compliance,
Governance, Risk, and Compliance (GRC), Benefits, GRC Program
Implementatio n, Cloud Security Alliance,
Self-Learning Topics: HIPAA, ISO, PCI 7 CO5

Page 23

VI Cloud Native
Security in
The Modern
Organization
Overview of Cloud Native Security, where it fits in the Modern
Organization, purpose of Security, Cloud Native Security Architecture,
Threats to Cloud Native Applications
3 R’s and 4 C's of Cloud Native Security
Cloud Native Security Controls, Cloud Native Security Tools,
Cloud Native security architecture principles, DevSecOps,
How to Measure the Impact of Security, Cloud -Native Application
Protection Platform (CNAPP)
Self Learning Topic: Case study on Secure the Cloud 6 CO6


Textbooks:
1. Cloud Security and Privacy: An Enterprise Perspective on Risks and Compliance by Tim Mather,
Subra Kumaraswamy, and Shahed Latif, O’Reilly
2. Cloud Native Security Cookbook: Recipes for a Secure Cloud 1st Edition by Josh Armitage , O’Reilly
3. Cloud Security: A Comprehensive Guide to Secure Cloud Computing by Ronald L. Krutz and Russell
Dean Vines, Wiley

References:
1. "Securing the Cloud: Cloud Computer Security Techniques and Tactics" by Vic (J.R.) Winkler,
SYNGRESS
2. "Identity and Access Management as a Service: Security as a Service" by Wei Meng Lee
3. Cloud Security for Dummies by Ted Coombs, O’Reilly

Online References:
1. https://www.coursera.org/learn/cloud -computing -security#about
2. https://www.coursera.org/specializat ions/cybersecurity -cloud
3. https://www.edx.org/course/cloud -computing -security
4. https://www.ibm.com/topics/cloud -security
5. https://www.vmware.com/topics/glossary/content/east -west -security.html
6. https://www.vmware.c om/topics/glossary/content/data -center -security.html
7. https://cloud.google.com/learn/what -is-disaster -recovery
8. https://www.splunk.com/en_us/blog/learn/cloud -native -security.html
Assessment:
Internal Assessment (IA) for 20 marks:
● IA will consist of Two Compulsory Internal Assessment Tests. Approximately 40% to 50% of syllabus
content must be covered in First IA Test and remaining 40% to 50% of syllabus content must be covered
in Second IA Test
Question paper format
● Question Pap er will comprise of a total of six questions each carrying 20 marks. Q.1 will be
compulsory and should cover maximum contents of the syllabus.
● Remaining questions will be mixed in nature (part (a) and part (b) of each question must be from
different modu les. For example, if Q.2 has part (a) from Module 3 then part (b) must be from any other
Module randomly selected from all the modules)
● A total of four questions needs to be answered.

Page 24

Course
Code Course Name Theory Practical Tutorial Theory Pract/Oral Tutorial Total
IoTCSBC
DO701 2
Software
Testing &
Quality
Assurance
(STQA) 03 -- -- 03 -- -- 03

Course Code Course
Name Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End
Sem.
Exam Test1 Test 2 Avg. of 2
Tests
IoTCSBCDO
7012 Software
Testing &
Quality
Assurance
(STQA) 20 20 20 80 -- -- -- 100

Course Objectives:
Sr. No. Course Objectives
The course aims:
1 To provide students with knowledge in Software Testing techniques.
2 To provide knowledge of Black Box and White Box testing techniques.
3 To provide skills to design test case plans for testing software.
4 To prepare test plans and schedules for testing projects.
5 To understand how testing methods can be used in a specialized environment.
6 To understand how testing methods can be used as an effective tool in providing quality assurance
concerning software.

Course Outcomes:
Sr. No. Course Outcomes Cognitive levels of
attainment as per
Bloom’s Taxonomy
On successful completion, of course, learner/student will be able to:
1 Investigate the reason for bugs and analyze the principles in software
testing to prevent and remove bugs. L1, L2, L3, L4
2 Understand various software testing methods and strategies. L1, L2
3 Manage the testing process and testing metrics. L1, L2, L3, L4
4 Understand fundamental concepts of software automation and use
automation tools. L1, L2
5 Apply the software testing techniques in the real time environment. L1, L2. L3
6 Use practical knowledge of a variety of ways to test software and quality
attributes. L1, L2. L3

Prerequisite: Programming Language (C++, Java), Software Engineering

Page 25

DETAILED SYLLABUS:

Sr.
No. Module Detailed Content Hours CO
Mapping
0 Prerequisite Software Engineering Concepts, Basics of programming
Language 02
I Testing
Methodology
Introduction, Goals of Software Testing, Software Testing
Definitions, Model for Software Testing, Effective Software
Testing vs Exhaustive Software Testing, Software Failure Case
Studies, Software Testing Terminology, Software Testing Life
Cycle (STLC), Software Testing methodology, Verification and
Validation, Verification requirements, Verification of high -level
design, Verification of low -level design, validation.

Self-learning Topics: Study any system/application, find
requirement specifications and design the system. Select software
testing methodology suitable to the application. 07 CO1
II Testing
Techniques
Dynamic Testing: Black Box Testing: Boundary Value Analysis,
Equivalence Class Testing, State Table Based testing, Cause -
Effect Graphing Based Testing, Error Guessing.
White Box Testing Techniques: need, Logic Coverage Criteria,
Basis Path Testing, Graph Matrices, Loop Testing, Data Flow
testing, Mutation testing. Static Testing.
Validation Activities: Unit validation, Integration, Function,
System, Acceptance Testing.
Regression Testing: Progressive vs. Regressive, Regression
Testing, Regression Testability, Objectives of Regression Testing,
Regression Te sting Types, Define Problem, Regression Testing
Techniques.

Self-learning Topics: Select the test cases (positive and negative
scenarios) for the selected system and Design Test cases for the
system using any two studied testing techniques. 09 CO2
III Managing the
Test
Process
Test Management: test organization, structure and of testing
group, test planning, detailed test design and test Specification.
Software Metrics: need, definition and Classification of software
matrices. Testing Metrics for Monit oring and Controlling the
Testing Process: attributes and corresponding metrics, estimation
model for testing effort, architectural design, information flow
matrix used for testing, function point and test point analysis.
Efficient Test Suite Management: m inimizing the test suite and its
benefits, test suite minimization problem, test suite prioritization
of its type, techniques and measuring effectiveness.

Self-learning Topics: Design quality matrix for your selected
system 08 CO3
IV Test
Automation Automation and Testing Tools: need, categorization, selection and
cost in testing tool, guidelines for testing tools.
Study of testing tools: JIRA, Bugzilla, TestDirector and IBM
Rational Functional Tester, Selenium etc.

Self-learning Topics: Write down t est cases, execute and manage
using studied tools 05 CO4

Page 26

V Testing for
specialized
environment
Agile Testing, Agile Testing Life Cycle, Testing in Scrum phases,
Challenges in Agile Testing
Testing Web based Systems: Web based system, web technology
evaluation, traditional software and web -based software,
challenges in testing for web -based software, testing web -based
testing.

Self-learning Topics: Study the recent technical papers on
software testing for upcoming technologies (Mobile, Cloud,
Blockchain, IoT) 04 CO5
VI Quality
Management
Software Quality Management, McCall’s quality factors and
Criteria, ISO 9000:2000, SIX sigma, Software quality
management

Self-learning Topics: Case Studies to Identify Quality Attributed
Relationships for different types of Applications (Web based,
Mobile based etc.) 04 CO6

Textbooks:

1. Software Testing Principles and Practices Naresh Chauhan Oxford Higher Education
2. Software Testing and quality assurance theory and practice by Kshirasagar Naik, Priyadarshi
Tripathy, Wiley Publication

References Books:

1. Effective Methods for Software Testing, third edition by Willam E. Perry, Wiley
Publication
2. Softw are Testing Concepts and Tools by Nageswara Rao Pustular , Dreamtech press

Online References:
1. www.swayam.gov.in
2. www.coursera.org
3. http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1099 -1689
4. https:/ /onlinecourses.nptel.ac.in/noc17_cs32/preview
5. https://www.youtube.com/channel/UC8w8_H_1uDfi2ftQx7a64uQ

Assessment:
Internal Assessment (IA) for 20 marks:
● IA will consist of Two Compulsory Internal Assessment Tests. Approximately 40% to 50% of
syllabus content must be covered in First IA Test and remaining 40% to 50% of syllabus content
must be covered in Second IA Test
Question paper format

● Question Pa per will comprise of a total of six questions each carrying 20 marks. Q.1 will be
compulsory and should cover maximum contents of the syllabus.
● Remaining questions will be mixed in nature (part (a) and part (b) of each question must be from
different mod ules. For example, if Q.2 has part (a) from Module 3 then part (b) must be from any
other Module randomly selected from all the modules)
● A total of four questions needs to be answered.

Page 27

Subject
Code Subject Name Theor
y Practical Tutoria
l Theor
y Practical
/Oral Tutoria
l Total
IoTCSBCDO
7013 IoT for Smart
Cities 03 -- -- 03 -- -- 03

Subject
Code Subject
Name Examination Scheme
Theory Marks Term
Wor
k Practica
l Oral Total Internal assessment End
Sem.
Exam Test
1 Test 2 Avg. of 2
Tests
IoTCSBCDO
7013 IoT for
Smart
Cities 20 20 20 80 -- -- -- 100

Course Objectives:
Sr. No. Course Objectives
The course aims:
1. Understand the concept and significance of smart cities and the various components and
characteristics that define them.
2. Explore the transformation of conventional cities into smart cities and the parameters used to
measure their level of "smartness".
3. Understand the collaboration between drones and the Internet of Things (IoT) in smart cities and
the implications for privacy security energy efficiency and public safety .
4. Develop an understanding of the system architecture design principles for IoT -based smart cities
including domain analysis reference architecture design and deployment view.
5. Examine the developm ent of Smart Seoul including its infrastructure government/municipal -
developed services citizen -developed services and smart city standardization.
6. Analyze real -world case studies of smart city applications in the areas of parking weather
monitoring forest fire detection and air pollution monitoring .


Course Outcomes:
After the course students will be able to

Page 28

Sr.
No. Course Outcomes Cognitive levels of
attainment as per
Bloom’s Taxonomy
On successful completion, of course, learner/student will be able to:
1 Define the concept of smart cities and explain their importance in the
modern world. L1, L2

2. Identify and describe the parameters used to measure the smartness of
cities. L2,L3
3. Propose energy -efficient solutions using drones and IoT in smart cities. L3,L4
4. Evaluate the effectiveness of different architectural approaches for IoT -
based smart cities. L2,L3
5. Generate ideas for innovative applications and solutions to improve
smart city infrastructure and services based on the case study of Smart
Seoul. L1,L2
6. Critically assess the impact and potential risks associated with the
implementation of smart city solutions in various domains. L2,L3

Prerequisites:
IoT Architecture and Protocols, RFID and Microcontrollers, Wireless Sensor Technologies

DETAILED SYLLABUS:
Sr.
No. Module Detailed Content Hours CO
Mappin
g
0 Prerequisite IoT architecture, protocols, design stages, applications.
I Introduction
to smart
cities Introduction, Characteristics of Smart Cities, Smart
Economy, Smart People Smart Governance Smart Mobility,
Smart Environment, Smart Living.

IoT-Based Solutions for Smart Cities , Smart Grid,Smart
Home, Transport and Traffic Management,Smart
Healt hcare

Challenges Ahead,Planning , Costs and Quality,Security
and Privacy, Risks. 3 CO1
II Journey
from
Conventional
Cities to
Smart Cities Types of cities, Background of smart cities, Artificial
intelligence for smart cities, Smart cities indexed
parame ters, Economy, Human capital, International
outreach, Mobility and transport, Environment, Technology,
Urban planning,Governance, Social cohesion,
Infrastructure. 5 CO2
III Collaborative
drone and
IoT for
improving Overview of the collaboration between drones and the IoT,
privacy and security issues, energy efficiency, data
collection in smart cities, improving life quality, public 5 CO3

Page 29

the
smartness of
smart cities. safety in smart cities, disaster management.
IV System
Architecture
Design of
IoT-Based
Smart Cities Domain Analysis, Reference Architecture Design ,
Architecture Framework and Viewpoint Selection,
Decomposition View, Layered View, Deployment View.
Case Study of Smart EV Charging. 8 CO4
V Case study:
Smart Cities
Seoul Smart Seoul, Smart Seoul Infrastructure,
Government/Municipal -developed Services,
Citizen -developed Services, NFC -based Mobile Payment,
Virtual Store,Smart City Standardization.

Artificial Intelligence Techniques for Smart City
Applications : Machine Learning Algori thms for Smart
Monitoring, Supervised Machine Learning Algorithms for
Smart Monitoring, Unsupervised and Hybrid Machine
Learning Algorithms for Smart Monitoring 7 CO5
VI
Case study
on smart city
applications Smart Parking,Weather monitoring, Forest fire detection,
Air pollution monitoring.
8 CO6

Text Books:
1. Internet of Things for Smart Cities: Technologies, Big Data and Security, WaleedEjaz,
AlaganAnpalagan, Springer briefs in electrical and computer engineering
2. Smart Cities and Construction Technologies, Edited by Sara Shirowzhan and Kefeng Zhang,
Intech open, Published in London, United Kingdom
3. Bahga, A. and Madisetti, V. (2015) Internet of Things: A Hands -On Approach., Universities
Press.
References:
1. Green Internet of Things for Smart Cities, Concepts, Implications, and Challenges, Edited By
Surjeet Dalal, Vivek Jaglan, Dac -Nhuong Le, CRC Press, 2021
2. Smart Cities: The Internet of Things, People and Systems, Schahram Dustdar , Stefan Nastić ,
Ognjen Šće kić, Springer, 2017.
3. IoT for Sustainable Smart Cities and Society, Edited By Joel J. P. C. Rodrigues , Parul Agarwal ,
Kavita Khanna , Springer, 2022.
Online References:
1. Survey on Collaborative Smart Drones and Internet of Things for Im proving Smartness of Smart
Cities, IEEE, https://ieeexplore.ieee.org/document/8795473

Page 30

2. System Architecture Design of IoT -Based Smart Cities, MDPI, https://www.mdpi.com/2076 -
3417/13/7/4173
3. Smart Cities Seoul, International Telecommunication Union, https://w ww.itu.int/dms_pub/itu -
t/oth/23/01/T23010000190001PDFE.pdf
4. Internet of Things for Smart Cities, IEEE INTERNET OF THINGS JOURNAL, VOL. 1, NO. 1,
FEBRUARY 2014, https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=6740844
5. Artificial Intelligence Techniques for Smart City Applications, Proceedings of the 18th
International Conference on Computing in Civil and Building Engineering, 2021, Volume 98, ISBN :
978-3-030-51294 -1


Assessment:
Internal Assessment (IA) for 20 marks:
● IA will consist of Two Compulsory Internal Assessment Tests. Approximately 40% to 50% of
syllabus content must be covered in First IA Test and remaining 40% to 50% of syllabus content must be
covered in Second IA Test.
➢ Question paper format:
● Question Paper will comprise of a total of six questions each carrying 20 marks Q.1 will be
compulsory and should cover maximum contents of the syllabus.
● Remaining questions will be mixed in nature (part (a) and part (b) of each question must be
from different modules. For example, if Q.2 has part (a) from Module 3 then part (b) must be from any
other Module randomly selected from all the modules).
● A total of four questions need to be answered.

Page 31

Course
Code Course Name Theory Practical Tutorial Theory Practical Tutorial Total
IoTC SBCD
O701 4 Supervisory Control and
Data acquisition (SCADA)
Security 03 -- -- 03 -- -- 03

Course
Code Course Name Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End Sem.
Exam Test1 Test
2 Avg. of 2
Tests
IoTC SBCD
O701 4 Supervisory Control and Data
acquisition (SCADA) Security 20 20 20 80 -- -- -- 100
Course Objectives:
The course aims:
Sr. No. Course Objectives
1 To understand SCADA systems operations and measuring the effectiveness of viable security controls.
2 To identify the challenges in securing current SCADA systems.
3 To interpret incident response, prioritization and notification in SCADA systems.
4 To plan SCADA contingency processes for Disaster Recovery and Business Continuity.
5 To assimilate Project Management for SCADA Systems.
6 Study new age SCADA systems utilities.

Course Outcomes:
On successful completion, of course, learner/student will be able to:
Sr. No. Course Outcomes Cognitive levels of
attainment as per Bloom’s
Taxonomy
1 Understand SCADA systems operations and measuring the effectiveness of
viable security controls. L1, L2
2 Identify and analyze the challenges in securing current SCADA systems. L1, L2, L4
3 Interpret incident response, prioritization, and notification in SCADA
systems. L1, L2, L3
4 Plan SCADA contingency processes for Disaster Recovery and Business
Continuity. L1, L2. L3
5 Assimilate Project Management for SCADA Systems. L1, L2, L3
6 Demonstrate new age SCADA systems utilities. L1, L2



Prerequisite: Computer Network and Security

Page 32

DETAILED SYLLABUS:

Sr.
No. Module Detailed Content Hours CO
Mapping
0 Prerequisite Computer Network and Security 02

I Industrial Control
Systems and Metrics
Framework


Evolution of Industrial Control Systems, ICS Industrial Sectors and
their Interdependencies, ICS Operation and Components, ICS
versus IT Systems Security, Metrics: Security group knowledge,
Attack group knowledge, Access, V ulnerabilities, Damage
potential, Detection and Recovery, Defining cybersecurity metrics.

Self-Study: Other Types of Control Systems 05 CO1
II The Cyberthreat to
SCADA systems and
Commercial product
vulnerabilities

Directed attacks, Thwarted attacks, Successful attacks, Identified
incidents, Microsoft: the leading supplier of software with
vulnerabilities, Other major vendors: Oracle, IBM Google, Adobe,
Apple, and Cisco.

Self-Study: Improvement of SCADA Security 07 CO2
III Incident Response and
SCADA




Difficulties with SCADA and incident response, Incident analysis,
Incident prioritization, Incident notification, choosing a
containment strategy, Evidence gathering and handling, Basic
forensics for standard computers, Identifying the attacker,
Erad ication and recovery, Evidence retention.

Self-Study: Case study: DHS (Department of Homeland Security) 07 CO3
IV
Disaster recovery and
business continuity of
SCADA




Business continuity process, Types of plans, Examples of SCADA
systems at risk, SCADA contingency planning process, SCADA
system contingency plan development, Recovery phase, Sequence
of recovery activities, Recovery procedures, Recovery escalation
and notification, Reconstitution phase, Plan appendices,
Maintenance of data security, integrity, and backup, Protection of
resources, Identification of alternate storage and processing
facilities.

Self-Study: Client/server systems and Telecommunications
systems 07 CO4
V Project management
for SCADA systems


Introduction, Areas of knowledge needed, Similarities and
differences with the SCADA community, managing stakeholders
and projects, how to be successful with SCADA implementations.

Self-Study: Case study: SCADA implementations 05 CO5
VI Supervisory control
applications &
Operator interface
Operating System Utilities, SCADA System Utilities, Program
Development Tools, Access -Control Mechanisms, Standard
System Displays, Logs and Reports.

Self-Study: Standardized APIs, Site/Industry –Specific Displays,
Historical Trending 06 CO6

Page 33

Textbooks:


1. Guide to Industrial Control Systems (ICS) Security, Revision 2 by Keith Stouffer, Victoria Pillitteri,
Suzanne Lightman, Marshall Abrams, Adam Hahn
2. Handbook of SCADA/Control Systems, Second Edition by Robert Radvanovsky, Jacob Brodsky
3. Cybersecurity for SCADA Systems, Second Edition by Willam Shaw
4. Cyber -security of SCADA and Other Industrial Control Systems By Edward J. M. Colbert, Alexander
Kott

References Books:

1. "Industrial Automation and Control System Security Principles" b y Ronald L. Krutz and Russell
Dean Vines
2. "SCADA Security: What's Broken and How to Fix It" by Robert Radvanovsky and Jacob Brodsky
3. "SCADA Security: Protecting Critical Infrastructure Systems" by Jack Whitsitt
4. "SCADA and Me: A Book for Children and Management" by Robert M. Lee

Online References:
1. https://www.inductiveautomation.com/resources/article/what -is-scada
2. https://www.dpstele.com/scada/introduction -fundamentals -implementation.php
3. https://www.parasyn.com.au/scada -services -rtu-solutions/#whataretheapplicationsusedinscada?
4. https://www. parasyn.com.au/scada -services -rtu-
solutions/#whatarethegreatestproblemswithscadasystems?
5. https://www.forcepoint.com/cyber -edu/scada -security


Assessment:
Internal Assessment (IA) for 20 marks:
● IA will consist of Two Compulsory Internal Assessment Tests. Approximately 40% to 50% of syllabus
content must be covered in First IA Test and remaining 40% to 50% of syllabus content must be covered
in Second IA Test
Question paper format

● Question Paper will comprise of a total of six questions each carrying 20 marks. Q.1 will be
compulsory and should cover maximum contents of the syllabus.
● Remaining questions will be mixed in nature (part (a) and part (b) of each question must be from
different modules. For example, if Q.2 has part (a) from Module 3 then part (b) must be from any other
Module randomly selected from all the modules)
● A total of four questions needs to be answered.

Page 34

Subject Code Subject
Name Theory Practical Tutorial Theory Practical/
Oral Tutoria
l Total
IoTCSBCDO702
1 Design a
Blockchain
Application
Architecture 03 -- -- 03 -- -- 03

Subject
Code Subject Name Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal Assessment End
Sem.
Exam Test1 Test 2 Avg. of 2
Tests
IoTCSBC
DO702 1 Design A Blockchain
Application
Architecture 20 20 20 80 -- -- -- 100

Course Objectives:
Sr. No. Course Objectives
1. To get acquainted with the concepts of Blockchain and the concepts of consensus in
Permissioned Blockchain.
2. To get familiar with the concepts of Ethereum Blockchain
3. To get familiar with the concepts of Hyperledger Fabric as an Enterprise Blockchain.
4. To understand scalability and interoperability concepts in blockchain.
5. To understand and compare various Blockchain Ecosystems and platforms
6. To analyze the applications and use cases of Blockchain

Course Outcomes:

Sr. No. Course Outcomes Cognitive levels of
attainment as per
Bloom’s Taxonomy
1 Describe the basic concepts of Blockchain and the knowledge of consensus
in Permissioned Blockchain. L2
2 Apply the fundamentals of Ethereum Blockchain towards developing
industrial solutions. L2
3 Understand and apply Enterprise based Blockchain with respect to
Hyperledger Fabric. L3
4 Interpret the scalability and interoperability concepts in blockchain. L3
5 Illustrate different blockchain platforms and their applications. L5
6 Apply the concepts of Blockchain towards different use -cases and
applications. L2

Page 35

Prerequisite: Introduction to Cryptography and Distributed Systems.
DETAILED SYLLABUS:
Sr.
No. Module Detailed Content Hours CO
Mapping
0 Prerequisite Introduction to Cryptography - Hash Functions, Public Key
Cryptography, Digital Signature.
Introduction to Distributed System s - Distributed Systems,
Benefits of Distributed Systems, Decentralized Vs Distributed,
CAP Theorem, BASE Properties 2 --
I Introduction to
Blockchain and
Consensus
Mechanism Fundamental concepts of blockchain, key characteristics,
history, generations blockchain vs traditional databases.
Consensus: Definition, requirements, characteristics,
algorithms: PoW, PoA, PoS, RAFT, Byzantine General
Problem, Practical Byzantine Fault Tolerance
Self-learning Topics: DAG, othe r consensus algorithms. 5 CO1
II Ethereum
Blockchain Introduction to Ethereum : Ethereum 1.0 and 2.0, Turing
completeness EVM and compare with bitcoin, Basics of Ether
Units, Ethereum Wallets: Structure of Transaction, Transaction
Nonce, Transaction GAS, Recipient, Values and Data,
Transmitting Values to EOA and Contracts.
Smart Contracts and Solidity: Development environment and
client, Basic of Solidity, Life cycle of Smart contract, Smart
Contract programming using solidity, Metamask (Ethereum
Wallet), Setting up a development environment, Use cases of
Smart Contract, Smart Contracts: Opportunities and Risk.
Smart Contract Deployment : Introduction to Truffle, Use of
Remix and test networks for deployment
Self-learning Topics: Smart contract development using Java or
Python. 10 CO2
III Hyperledger Basic definition, tools and frameworks, Hyperledger Fabric –
Components, Transaction Flow, Membership and Identity
Management, Network Setup, Certificate Authority, Nodes,
Chain codes, Channels, Consensus: Solo and Kafka, Challenges:
Interoperability and S calability of blockchain
Self-learning Topics: Deploy from scratch, Hyperledger
Composer - Application Development and Network
Administration. 6 CO3
IV Security,
Scalability and
Interoperability Introduction to scalability and Interoperability:
understanding concepts of blockchain scalability and
interoperability, benefits, key challenges, potential solutions,
cross -chain technology, applications .
Security and Privacy challenges of blockchain .
Self-learning Topics: white -papers addressing challen ges and
solutions for scalability and interoperability. 6 CO3
V Blockchain
Platforms and
Polkadot Introduction, basic working, advantages and disadvantages, with
respect to EOS, Corda, Multichain, Quorum, Polkadot,
COSMOS. Introduction to Polkadot , evolution and working of
Polkadot, the Network and governance on polkadot network.
Self-learning Topics : Other blockchain platforms 6 CO5
VI Blockchain Use
Cases Blockchain in Financial Service - Payments and Secure Trading,
Blockchain in Supply Chain and Other Industries
Blockchain in Government - Advantages, Use Cases, Digital
Identity, Tax Payments and Land Registry Records 4 CO6

Page 36

Text Books:
1. Antonopoulos, Andreas M. Mastering Bitcoin: Programming the open blockchain . " O'Reilly Media, Inc.", 2017.
2. Blockchain Scalability & Interoperability Bane -To-Boon: By Harish Jaggi & Raj Jha.
3. Blockchain Technology Kindle Edition by Chandramouli Subramanian , Asha A George , Abhilash K
A, Meena Karthikeyan .
4. Mastering Ethereum - Building Smart Contracts and DApps, Andreas M. Antonopoulos and Dr. Gavin Wood,
O'Reilly Media, Inc.", 2019.
5. Mastering Blockchain, Third Edition, 2020 Packt Publishing, Imran Bashir
6. Blockchain with Hyperledger Fabric, Second Edition, 2020 Packt Publishing, Nitin Gaur et.al .
7. POLKADOT FOR BEGINNERS A non -technical guide to decentralization, blockchains, and Polkadot,
Gbaci.

References:
1. Kube, Nicolas. "Daniel Drescher: Blockchain basics: a non -technical introduction in 25 steps: Apress, 2017, 255
pp, ISBN: 978 -1-4842 -2603 -2." (2018): 329 -331.
2. Blockchain by Melanie Swan, O’Reilly
3. Zero to Blockchain - An IBM Redbooks course, by Bob Dill, David Smits
4. Baset, Salman A., et al. Hands -on blockchain with Hyperledger: building decentralized applications with
Hyperledger Fabric and composer . Packt Publishing Ltd , 2018.
5. Gaur, Nitin, et al. Blockchain with hy perledger fabric: Build decentralized applications using hyperledger
fabric 2 . Packt Publishing Ltd, 2020.
6. Mastering Bitcoin: Unlocking Digital Cryptocurrencies, by Andreas Antonopoulos

Online References:
1. Live Demo : https://andersbrownworth. com/blockchain/
2. Udemy Course - Blockchain A -Z™: Learn How To Build Your First Blockchain
https://www.udemy.com/course/build -your-blockchain -az/
3. Chakraborty, Sandip, and Praveen Jayachandran. "Blockchain -Architecture, Design and Use cases." NPTEL
Course Lecture (2018).
https://www.youtube.com/watc h?v=mzPoUjQC4WU&list=PLHRLZtgrF2jl8yqucJsMFqh5XpRLTgCI4
4. https://101blockchains.com/blockchain -scalability -solutions/
5. https://crypto.com/university/blockchain -scalability
6. https://cointelegraph.com/learn/what -is-blockchain -interoperability -a-beginners -guide -to-cross -chain -
technology
7. https://www.geeksforgeeks.org/blockchain -interoperability/
8. https://www.eublockchainforum.eu/sites/default/files/reports/report_scalaibility_06_03_2019.pdf

Page 37

Assessment:
Internal Assessment (IA) for 20 marks:
● IA will consist of Two Compulsory Internal Assessment Tests. Approximately 40% to 50% of syllabus
content must be covered in First IA Test and remaining 40% to 50% of syllabus content must be covered in
Second IA Test
Question paper format
● Question Paper will comprise of a total of six questions each carrying 20 marks Q.1 will be compulsory
and should cover maximum contents of the syllabus.
● Remaining questions will be mixed in nature (part (a) and part (b) of each question must be from different
modules. For example, if Q.2 has part (a) from Module 3 then part (b) must be from any other Module
randomly selected from all the modules)
● A total of four questions needs to be answered.

Page 38

Course
Code Course Name Theory Practic
al Tutori
al Theory Practical Tutorial Total
IoTCSBCD
O702 2 User Interface
Design with
Security 03 -- -- 03 -- -- 03

Course
Code Course Name Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End Sem.
Exam Test1 Test
2 Avg. of 2
Tests
IoTCSBCD
O702 2 User Interface
Design with
Security 20 20 20 80 -- -- -- 100

Course Objectives:
Sr. No. Course Objectives
1 To stress the importance of good interface design.
2 To understand the importance of human psychology as well as social and emotional aspect in designing good
interfaces.
3 To learn the techniques of data gathering, establishing requirements, analysis and data interpretation.
4 To learn the techniques for prototyping and evaluating user experiences.
5 To understand interaction design process and bring out the creativity in each student – build innovative
applications that are usable, effective and efficient for intended users.
6 To understand the role of security in User interaction design.
Course Outcomes:
Sr.
No. Course Outcomes Cognitive levels of attainment as
per Bloom’s Taxonomy
On successful completion, of course, learner/student will be able to:
1 Identify and criticize bad features of interface designs. L4
2 Predict good features of interface designs. L5
3 Illustrate and analyze user needs and formulate user design specifications. L4
4 Interpret and evaluate the data collected during the process. L2, L5
5 Evaluate designs based on theoretical frameworks and methodological
approaches and will be able to produce/show better techniques to improve the
user interaction design interfaces. L5
6 Evaluate designs based on cyber security aspects. L5

Prerequisite: Basics of Cyber Security, Software Engineering concepts and any programming Language

Page 39

DETAILED SYLLABUS:
Sr.
No. Module Detailed Content Hours CO
Mapping
0 Prerequisite Basics of Cyber Security, Software Engineering concepts and any
programming Language
Self-learning Topics: Web design languages 1 --
I Introduction To
Interaction Design Good And Poor Design, Interaction Design, The User Experience,
The Process of Interaction Design, interaction Design and The User
Experience
Self-learning Topics: Study of Various interactive day to day
application 5 CO1
II Understanding And
Conceptualizing
Interaction
Understanding The Problem Space and Conceptualizing Design,
Conceptual Model, Interface Types, Cognitive Aspects, Social
Interaction and The Emerging Social Phenomena, Emotions and
The User Experience, Expressive And Frustrating Interfaces,
Persuasive Technologies
Self-learning Topics: Study of Various interactive Interface Types 5 CO2
III Data Processing
Establishing Requirements, Five Key Issues, Techniques for Data
Gathering, Data Analysis Interpretation and Presentation, Task
Description and Task Analysis
Self-learning Topics: Any case study of how to gather
requirements. (eq.BE Project ) 6 CO3
IV Process Of Interaction
Design and Design
Rules and Industry
Standards
Interaction Design Process, Prototyping and Conceptual Design,
Interface Metaphors and Analogies, Design Principles, Principles
to Support Usability, Standards And Guidelines, Golden Rules and
Heuristics, ISO/IEC Standards
Self-learning Topics: Study of t wo websites with usability
concepts. Study experiments on industry standards and design
principles. principles. https://xd.adobe.com/ideas/career -tips/15 -
rules -every -ux-designer -know/ 7 CO4
V Evaluation Techniques
and Framework
The Why, what, Where and When of Evaluation, Types Of
Evaluation, Case Studies DECIDE Framework, Usability Testing,
Conducting Experiments, Field Studies, Heuristic Evaluation and
Walkthroughs, Predictive Models.
Self-learning Topics: Evaluation of any GUI with usability
principles. 7 CO5
VI Usability Design and
Evaluation for Privacy
and Security Solutions
and Secure Systems Usability in the Software and Hardware Life Cycle: Unique Aspects
of HCI and Usability in the Privacy and Security Domain, Usability
in Requirements, Usability in Design and Develo pment, Usability
in Post release, Guidelines and Strategies for Secure Interaction
Design, Design Guidelines, Authorization, Communication,
Design Strategies, Security by Admonition and Security by
Designation, Applying the Strategies to Everyday Security
Problems, Fighting Phishing at the User Interface
Self-learning Topics: Any case study of how to check Cyber
Security Guidelines ( eg. BE Project) 8 CO6

Page 40

Textbooks:
1. Interaction Design, by J. Preece, Y. Rogers and H. Sharp. ISBN 0-471-49278 -7.
2. Security and Usability by Lorrie Faith Cranor, Simson Garfinkel, Publisher(s): O'Reilly Media,
Inc. ISBN: 9780596553852 ( Chapter 4 , 13 & 14)
3. Jeff Johnson, “Designing with the mind in mind”, Morgan Kaufmann Publication.
4. Wilbert O. Galitz, “The Essential Guide to User Interface Design”, John Wiley & Sons, Second
Edition 2002.
5. Human Computer Interaction, by Alan Dix, Janet Finlay, Gregory D Abowd, Russell Beale
6. Alan Cooper, Robert Reimann, David Cronin, “About Face3: Essentials of Int eraction design”,
Wiley publication.
7. Wilbert O. Galitz, “The Essential Guide to User Interface Design”, Wiley publication.

References:
1. Nilakshi Jain, Dhanajay R kalbande UI DESIGN: Key to Captivate User Understanding, STBGEN
Learning
2. The UX Book, by Rex Hartson and Pardha S Pyla.
3. Donald A. Norman, “The design of everyday things”, Basic books.
Online References:
1. https://onlinecourses.nptel.ac.in/noc21_ar05/preview
2. https://nptel.ac.in/courses/124/107/124107008/
3. https://nptel.ac.in/noc/courses/noc19/SEM1/noc19 -ar10/
4. https://nptel.ac.in/courses/107/103/107103083/
5. https://www.youtube.com/watch?v=6C2Ye1makdY&list=PLW -zSkCnZ -
gD5TDfs1eL5EnH2mQ0f9g6B
6. https://xd.adobe.com/ideas/process/

Assessment:
Internal Assessment (IA) for 20 marks:
● IA will consist of Two Compulsory Internal Assessment Tests. Approximately 40% to 50% of syllabus
content must be covered in First IA Test and remaining 40% to 50% of syllabus content must be covered
in Second IA Test
Question paper format

● Question Paper will comprise of a total of six questions each carrying 20 marks. Q.1 will be
compulsory and should cover maximum contents of the syllabus.
● Remaining questions will be mixed in nature (part (a) and part (b) of each question must be from
different modules. For example, if Q.2 has part (a) from Module 3 then part (b) must be from any other
Module randomly selected from all the modules)
● A total of four questions needs to be answered.

Page 41

Subject Code Subject Name
Theory Practical Tutorial Theory Oral Tutorial Total
IoTCSBCDO70
23 Enterprise IoT
Cyber Security 03 -- -- 03 -- -- 03

Subject
Code Subject
Name Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End
Sem.
Exam Test1 Test 2 Avg. of 2
Tests
IoTCSBC
DO7023 Enterprise
IoT Cyber
Security 20 20 20 80 -- -- -- 100

Course Objectives: The course aims:
1. To learn fundamentals of Enterprise IoT, vulnerabilities, attacks and countermeasures for IoT systems.
2. To gain knowledge in security engineering for IoT development and lifecycle.
3. To understand the cryptographic fundamentals for IoT security engineering.
4. To develop a comprehensive understanding of challenges and sol utions in secured identity management.
5. To gain knowledge of the different privacy regulations and compliance requirements .
6. To analyze various case studies and applications for Enterprise IoT.

Course Outcomes: On successful completion of course, lear ner/student will be able to:
Sr. No. Course Outcomes Cognitive levels of
attainment as per
Bloom’s Taxonomy
On successful completion, of course, learner/student will be able to:
1 Discuss fundamentals of Enterprise IoT, vulnerabilities, attacks and threats in IoT
systems L2

2. Illustrate IoT security life cycle L4
3. Examine various cryptographic controls for IoT protocols. L4
4. Evaluate the identity and access management solution for IoT security. L5
5. Identify applicable privacy regulations and compliance requirements for data in
IoT environments L2
6. Evaluate various case studies and applications for Enterprise IoT L5

Prerequisite: Knowledge of IoT and Cryptography
DETAILED SYLLABUS

Page 42

Sr. No. Module Detailed Content Hours CO
Mapping
0 Prerequisite Basics of IoT and cryptography 2
I INTRODUCTION TO
ENTERPRISE IOT
CYBER SECURITY Fundamentals of IOT in Enterprise, IoT device lifecycle.
Security Requirements in IoT Architecture, Security in
Enabling Technologies.
Primer on threats, vulnerability and risks (TVR), Primer on
attacks and countermeasures.
Today’s IoT attacks.
Self Learning Topics : Threat modeling an IoT System. 5 CO1
II IOT SECURITY
ENGINEERING AND
DEVELOPMENT Building security into design and development - Security in
Agile developments
Secure design - Safety and security design, Process and
agreements, Technology selection – security products and
services
IoT security lifecycle – Implementation and integration,
operatio ns and maintenance, Dispose.
Self Learning Topics: Cyber attack on Industrial control
system, ransomware attack on healthcare enterprise
“Wannacry” case study 7 CO2
III CRYPTOGRAPHIC
FUNDAMENTALS
FOR IOT SECURITY Cryptographic primitives and its role in s ecuring the IoT.
Cryptographic module principles, key management
fundamentals.
Cryptographic controls built into IoT communication and
messaging protocols
IoT Node Authentication
Self Learning Topics: Future directions of IoT and
Cryptography (Including blockchain for IoT security) 6 CO3
IV IDENTITY & ACCESS
MANAGEMENT
SOLUTIONS FOR
SECURE IOT Identity lifecycle
Authentication credentials – Passwords, Symmetric keys,
Certificates, Biometrics
IoT IAM infrastructure –802.1X, PKI for IoT
Authorization and access control – OAuth 2.0, publish/
subscribe protocols and communication protocols
Self Learning Topics: Authentication and authorization
framework of IIoT 6 CO4
V MITIGATING IOT
PRIVACY CONCERNS
AND COMPLIANCE
MONITORING Privacy challenges introduced by the IoT, Performing an IoT
Privacy Impact Assessment (PIA) , Privacy by Design (PbD)
principles, Privacy engineering recommendations
IoT Compliance, challenges associated with IoT compliance,
examin ing compliance standard support for IoT
Self Learning Topics: Differential privacy in Industrial IoT 7 CO5
VI ENTERPRISE IOT: CASE
STUDIES AND
APPLICATION Cleaning Service Industry and Technology, Global Cold Chain
Management, Intelligent Lot Tracking, In dustrial Internet
Consortium Testbeds 6 CO6


Text Books:

Page 43

1. "Enterprise IoT: Strategies and Best Practices for Connected Products and Services" by Dirk Slama, Frank
Puhlmann, Jim Morrish, and Rishi M. Bhatnagar, O′Reilly
2. “Practical Internet of Things Security” by Brian Russell, Drew Van Duren, and John Sammons, PACKT
Publishing
3. "Securing the Internet of Things" by Shancang Li, Li Da Xu, and Liming Chen, SYNGRESS

References:
1. Security and Privacy in Internet of Things (IoTs) Models, Algorithms, and Implementations by FEI HU, CRC
Press
2. Security, Privacy and Trust in the IoT Environment by Zaigham Mahmood, Springer, ISBN: 9783030180744,
2019.
3. Ollie Whitehouse, “Security of Things: An Implementers’ Guide to Cy ber-Security forInternet of Things
Devices and Beyond”, NCC Group, 2014
4. “Practical Industrial Internet of Things Security”, By Sravani Bhattacharjee, PACKT Publishing.
Online References:

1. https://www.coursera.org/learn/iot -cyber -security
2. https://www.ed x.org/course/cybersecurity -and-privacy -in-the-iot

Assessment:
Internal Assessment (IA) for 20 marks:
● IA will consist of Two Compulsory Internal Assessment Tests. Approximately 40% to 50% of
syllabus content must be covered in First IA Test and remaining 40% to 50% of syllabus content must be
covered in Second IA Test.
➢ Question paper format:
● Question Paper will comprise of a total of six questions each carrying 20 marks Q.1 will be
compulsory and should cover maximum contents of the syllabus.
● Remaining que stions will be mixed in nature (part (a) and part (b) of each question must be
from different modules. For example, if Q.2 has part (a) from Module 3 then part (b) must be from any
other Module randomly selected from all the modules).
● A total of four quest ions need to be answered.

Page 44

Course
Code Subject Name Theory Practical Tutorial Theory Practical
/Oral Tutorial Total
IoTCSBCDO
7024 Software
Engineering &
Testing
Methodology
for IoT 03 -- -- 03 -- -- 03

Subject
Code Subject Name Examination Scheme
Theory Marks
Term
Work Practic
al Oral Total Internal assessment End
Sem.
Exam Test1 Test 2 Avg. of
2 Tests
IoTCSBCDO
7024 Software
Engineering
& Testing
Methodolog
y for IoT 20 20 20 80 -- -- -- 100

Course Objectives:
1. To provide the knowledge of the new process models and trends for IoT based software engineering practices.
2. To acquire skills on web based IoT application development
3. To gain the ability to identify the challenges in IoT to automate the real -time problems.
4. To acquire knowledge about various software test planning and techniques for IoT.

Course Outcomes: On successful completion of course, learners will be able to:

Sr.
No. Course Outcomes Cognitive levels of
attainment as per Bloom’s
Taxonomy
On successful completion, of course, learner/student will be able to:
1 Apprehend new process models and trends for IoT based software
engineering practices. L1

2. Design and model an IoT system using UML diagrams. L3,L4
3. Understand the challenges in IoT to automate the real -time
problems. L1, L2
4. Understand IoT based testing concepts and challenges. L1,L2
5. Identify different IoT testing planning and strategies. L1,L2
6. Explore various IoT testing techniques. L3,L4

Prerequisite:
Software Engineering , IoT Architecture and Protocols

Page 45

DETAILED SYLLABUS
Sr.
No. Module Detailed Content
Hours CO
Mapping
0 Prerequisite Process models in Software Engineering: Prescriptive,
evolutionary, and agile process models, UML Diagrams, IoT
devices and protocols. 2
I IoT Based
Software
Engineering New process model for IoT based Software Engineering:
Introduction, Layers of IoT, IoT based SDLC, Identifying
Business nee ds through IoT, IoT in various domains.
Introduction to trends in integrating IoT into Software
Engineering practices : DevOps in IoT, DevSecOps in IoT,
Integrating security into IoT, Machine Learning and AI in
IoT of Software Engineering practices. 6 CO1
II Modelling &
Design of IoT
System Modeling of IoT system using UML diagrams: IoT
Software Engineering, UML representations of IoT
Systems: Use case diagram, class diagram, interaction
diagrams, and physical diagrams,
Architecture design of IoT system, Cr yptographic
approaches, Machine Learning approaches.
8 CO2
III Web Based IoT
Application
Development Introduction to web based IoT application
development , IoT layered architecture for web
application development, challenges of IoT application
development, End -to-end complete IoT Solution. 5 CO3
IV Introduction to
IoT Testing Challenges in IoT Testing , advanced IoT device
challenges, IoT development -test-security -operation
lifecycle, Verification & Validation testing concepts,
factors and keys for IoT testing. 4 CO4
V IoT Test
Planning &
Strategy Basics of IoT Test Planning , IoT test planning &
strategy for hardware & software, Agile/DevOps test
lifecycle, Product and Development Lifecycle Impacts
on Test Planning – DevOps and Agile, V & V activities,
IoT test planning: Regression test cases, OTS hardware
and software, Secur ity and critical quality factors, IoT
strategy. 8 CO5
VI IoT Testing
Techniques and
Practices Techniques, practices, levels and types of testing to
apply to IoT , Functional test design techniques,
Exploratory testing, structural testing, industrial test
practices, IoT levels of testing related to lifecycle
phases, test planning for Agile Team. 6 CO6

Text Books:
1. Jon Duncan Hagar, IoT System Testing: An IoT Journey from Devices to Analytics and the Edge, Apress 2022.
2. D. Jeya Mala, Integrating the Internet of Things into Software Engineering Practices , IGI Global 2019.
References:
1. Sudham Sudhakar, Testing IoT: Build and Implement Test Automation and Performance Testing for IoT
Systems .
2. Aaron Guzman, Aditya Gupta, IoT Penetration Testing Cookbo ok: Identify vulnerabilities and secure your
smart devices Paperback – Import, 29 November 2017.

Page 46

3. Yogesh Singh, Software Testing, Cambridge University Press, 2012.
4. Mauro Pezze, Michal Young: Software Testing and Analysis – Process, Principles and Tec hniques , Wiley India,
2009.
5. Haengkon Kim, Roger Lee, Software Engineering in IoT, Big Data, Cloud and Mobile Computing, Springer
Nature, 2020.

Online References:
1. https://bytebeam.io/blog/iot -software -testing -guide/
2. www.omg.org/spec/UML/2.5.1/About -UML/
3. https://www.softwaretestinghelp.com/internet -of-things -iot-testing/
4. https://www.techarcis.com/whitepapers/security -testing -in-iot/
5. https://dl.acm.org/doi/abs/10.1145/3356317.3356326
6. https://yalantis.com/blog/iot -testing -guide/



Assessment:
Internal Assessment (IA) for 20 marks:
● IA will consist of Two Compulsory Internal Assessment Tests. Approximately 40% to 50% of
syllabus content must be covered in First IA Test and remaining 40% to 50% of syllabus content must be
covered in Second IA Test.
➢ Questio n paper format:
● Question Paper will comprise of a total of six questions each carrying 20 marks Q.1 will be
compulsory and should cover maximum contents of the syllabus.
● Remaining questions will be mixed in nature (part (a) and part (b) of each question must be
from different modules. For example, if Q.2 has part (a) from Module 3 then part (b) must be from any
other Module randomly selected from all the modules).
● A total of four questions need to be answered.

Page 47

Course Code Course Name Theory Practical Tutorial Theory Oral Tutorial Total
ILO7011 Product Life
Cycle
Management 03 -- -- 03 -- -- 03

Course Code Course Name Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment
End Sem.
Exam Test1 Test 2 Avg. of 2
Tests
ILO7011 Product Life
Cycle
Management 20 20 20 80 -- -- -- 100
Course Objectives:

Sr. No. Course Objectives:
The course aims:
1 To familiarize the students with the need, benefits and components of PLM
2 To acquaint students with Product Data Management & PLM strategies
3 To give insights into new product development program and guidelines for designing and
developing a product
4 To familiarize the students with Virtual Product Development
Course Outcomes:
Sr. No. Course Outcomes Cognitive levels of attainment as
per Bloom’s Taxonomy
On successful completion, of course, learner/student will be able to:
1 Gain knowledge about phases of PLM, PLM strategies and
methodology for PLM feasibility study and PDM implementation L1
2 Illustrate various approaches and techniques for designing and
developing products L3, L4
3 Apply product engineering guidelines / thumb rules in designing
products for moulding, machining, sheet metal working etc. L3
4 Acquire knowledge in applying virtual product development tools
for components, machining and manufacturing plant. L3

Page 48

Module
Detailed Contents
Hrs



01 Introduction to Product Lifecycle Management (PLM): Product Lifecycle
Management (PLM), Need for PLM, Product Lifecycle Phases, Opportunities of
Globalization, Pre -PLM Environment, PLM Paradigm, Importance & Benefits of PLM,
Widespread Impact of PLM, Focus and Application, A PLM Project, Starting the PLM
Initiative, PLM Applications
PLM Strategies: Industrial strategies, Strategy elements, its identification, selection and
implementation, Developing PLM Vision and PLM Strategy,
Change management for PLM 10





02 Product Design: Product Design and Development Process, Engineering Design,
Organization and Decomposition in Product Design, Typologies of Design Process
Models, Reference Model, Product Design in the Context of the Product Development
Process, Relation with the Development Process Plannin g Phase, Relation with the Post
design Planning Phase, Methodological Evolution in Product Design, Concurrent
Engineering, Characteristic Features of Concurrent Engineering, Concurrent Engineering
and Life Cycle Approach, New Product Development (NPD) and Strategies, Product
Configuration and Variant Management, The Design for X System, Objective Properties
and Design for X Tools, Choice of Design for X Tools and Their Use in the Design
Process 09

03 Product Data Management (PDM): Product and Product Data, PDM systems and
importance, Components of PDM, Reason for implementing a PDM system,
financial justification of PDM, barriers to PDM implementation 05
04 Virtual Product Development Tools: For components, machines, and
manufacturing plants, 3D CAD systems and realistic rendering techniques, Digital
mock -up, Model building, Model analysis, Modeling and simulations in Product Design,
Examples/Case studies 05
05 Integration of Environmental Aspects in Product Design: Sustainable
Development, Design for Environment, Need for Life Cycle Environmental Strategies,
Useful Life Extension Strategies, End -of-Life Strategies, Introduction of Environmental
Strategies into the Design Process, Life Cycle Environmental Stra tegies and
Considerations for Product Design 05


06 Life Cycle Assessment and Life Cycle Cost Analysis: Properties, and Framework of Life
Cycle Assessment, Phases of LCA in ISO Standards, Fields of Application and Limitations
of Life Cycle Assessment, Cost Analysis and the Life Cycle Approach, General
Framework for LCCA, Evolution of Models for Product Life Cycle Cost Analysis 05

Page 49

Assessment :

Internal:
Assessment consists of two tests out of which; one should be compulsory class test and the other is either a class
test or assignment on live problems or course project.

End Semester Theory Examination:
Some guidelines for setting up the question paper. Minimum 80% syllabus should be covered in question papers
of end semester examination. In question paper weightage of each module will be proportional to number of
respective lecture ho urs as mention in the syllabus.
1. Question paper will comprise of total six question
2. All question carry equal marks
3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from module 3 then part (b)
will be from any module other than module 3)
4. Only Four question need to be solved.


REFERENCES:

1. John Stark, “Product Lifecycle Management: Paradigm for 21st Century Product Realisation”, Springer -
Verlag, 2004. ISBN: 1852338105
2. Fabio Giudice, Guido La Rosa, AntoninoRisitano, “Product Design for the environment -A life cycle
approach”, Taylor & Francis 2006, ISBN: 0849327229
3. SaaksvuoriAntti, Immonen Anselmie, “Product Life Cycle Management”, Springer, Dreamtech, ISBN:
3540257314
4. Michael Grieve, “Product Lifecycle Management: Driving the next generation of lean thinking”, Tata
McGraw Hill, 2006, ISBN: 0070636265

Page 50

Course Code Course Name Theory Practical Tutorial Theory Oral Tutorial Total
ILO7012 Reliability
Engineering 03 -- -- 03 -- -- 03

Course
Code Course Name Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment
End Sem.
Exam Test1 Test 2 Avg. of 2
Tests
ILO7012 Reliability
Engineering 20 20 20 80 -- -- -- 100

Sr. No. Course Objectives:
The course aims:
1 To familiarize the students with various aspects of probability theory
2 To acquaint the students with reliability and its concepts
3 To introduce the students to methods of estimating the system reliability of simple and complex
systems
4 To understand the various aspects of Maintainability, Availability and FMEA procedure
Course Outcomes:
Sr. No. Course Outcomes Cognitive levels of
attainment as per Bloom’s
Taxonomy
On successful completion, of course, learner/student will be able to:
1 Understand and apply the concept of Probability to engineering problems L1, L3
2 Apply various reliability concepts to calculate different reliability parameters L3
3 Estimate the system reliability of simple and complex systems L5
4 Carry out a Failure Mode Effect and Criticality Analysis L4

Page 51

Module
Detailed Contents
Hrs


01 Probability theory: Probability: Standard definitions and concepts; Conditional
Probability, Baye’s Theorem.
Probability Distributions: Central tendency and Dispersion; Binomial, Normal,
Poisson, Weibull, Exponential, relations between them and their significance.
Measures of Dispersion: Mean, Median, Mode, Range, Mean Deviation,
Standard Deviation, Variance, Skewness and Kurtosis.

08


02 Reliability Concepts: Reliability definitions, Importance of Reliability, Quality
Assurance and Reliability, Bath Tub Curve.
Failure Data Analysis: Hazard rate, failure density, Failure Rate, Mean Time to Failure
(MTTF), MTBF, Reliability Functions.
Reliability Hazard Models: Constant Failure Rate, linearly increasing, Time
Dependent Failure Rate, Weibull Model. Distribution fun ctions and reliability analysis.

08
03 System Reliability: System Configurations: Series, parallel, mixed configuration, k out
of n structure, Complex systems. 05

04 Reliability Improvement: Redundancy Techniques: Element redundancy, Unit
redundancy, Standby redundancies. Markov analysis. System Reliability Analysis –
Enumeration method, Cut -set method, Success Path method, Decomposition method.
08


05 Maintainability and Availability: System downtime, Design for Maintainability:
Maintenance requirements, Design methods: Fault Isolation and self -diagnostics, Parts
standardization and Interchangeability, Modularization and Accessibility, Repair Vs
Replacement. Availability – qualitative aspects.
05

06 Failure Mode, Effects and Criticality Analysis: Failure mode effects analysis,
severity/criticality analysis, FMECA examples. Fault tree construction, basic symbols,
development of functional reliability block diagram, Fau1t tree analysis and Event tree
Analysis
05

Assessment

Internal:
Assessment consists of two tests out of which; one should be compulsory class test and the other is either a
class test or assignment on live problems or course project.

End Semester Theory Examination:
Some guidelines for setting up the question paper. Minimum 80% syllabus should be covered in question papers
of end semester examination. In question paper weightage of each module will be proportional to number of
respective lecture hours as mention in t he syllabus.
1. Question paper will comprise of total six question
2. All question carry equal marks
3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from module 3 then part (b)
will be from any module other than module 3)
4. Only Four question need to be solved.
REFERENCES:

1. L.S. Srinath, “Reliability Engineering”, Affiliated East -Wast Press (P) Ltd., 1985.
2. Charles E. Ebeling, “Reliability and Maintainability Engineering”, Tata McGraw Hill.
3. B.S. Dhillion, C. Singh, “Engineering Reliability”, John Wiley & Sons, 1980.
4. P.D.T. Conor, “Practical Reliability Engg.”, John Wiley & Sons, 1985.
5. K.C. Kapur, L.R. Lamberson, “Reliability in Engineering Design”, John Wiley & Sons.
6. Murray R. Spiegel, “Probability and Statistics”, Tata McGraw -Hill Publishing Co. Ltd.

Page 52

Course
Code Course Name Theory Practical Tutorial Theory Oral Tutorial Total
ILO7013 Management
Information
System 03 -- -- 03 -- -- 03

Course Code Course Name Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment
End Sem.
Exam Test1 Test 2 Avg. of 2
Tests
ILO7013 Management
Information
System 20 20 20 80 -- -- -- 100
Course Objectives:

Sr. No. Course Objectives:
The course aims:
1 The course is blend of Management and Technical field.
2 Discuss the roles played by information technology in today’s business and define various technology
architectures on which information systems are built
3 Define and analyze typical functional information systems and identify how they meet the needs of the
firm to deliver efficiency and competitive advantage
4 Identify the basic steps in systems development
Course Outcomes:
Sr. No. Course Outcomes Cognitive levels of attainment as
per Bloom’s Taxonomy
On successful completion, of course, learner/student will be able to:
1 Explain how information systems Transform Business L2, L4, L5
2 Identify the impact information systems have on an organization L1
3 Describe IT infrastructure and its components and its current trends L1, L2
4 Understand the principal tools and technologies for accessing
information from databases to improve business performance and
decision making L1
5 Identify the types of systems used for enterprise -wide knowledge
management and how they provide value for businesses. L1

Page 53

Module
Detailed Contents
Hrs

01 Introduction To Information Systems (IS): Computer Based Information Systems, Impact
of IT on organizations, Imporance of IS to Society.
Organizational Strategy, Competitive Advantages and IS.
4

02 Data and Knowledge Management: Database Approach, Big Data, Data warehouse and
Data Marts, Knowledge Management.
Business intelligence (BI): Managers and Decision Making, BI for Data analysis.
and Presenting Results
7
03 Ethical issues and Privacy: Information Security. Threat to IS, and Security Controls 7

04 Social Computing (SC): Web 2.0 and 3.0, SC in business -shopping, Marketing,
Operational and Analytic CRM , E-business and E -commerce – B2B B2C. Mobile
commerce.
7
05 Computer Networks Wired and Wireless technology, Pervasive computing,
Cloud computing model. 6

06 Information System within Organization: Transaction Processing Systems, Functional
Area Information System, ERP and ERP support of Business Process. Acquiring
Information Systems and Applications: Various System development life cycle models.
8


Assessment :

Internal:
Assessment consists of two tests out of which; one should be compulsory class test and the other is either a
class test or assignment on live problems or course project.


End Semester Theory Examination:
Some guidelines for setting up the question paper. Minimum 80% syllabus should be covered in question papers
of end semester examination. In question paper weightage of each module will be proportional to number of
respective lecture hours as mention in the syllabus.
1. Question paper will comprise of total six question
2. All question carry equal marks
3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from module 3 then part (b)
will be from any module other than module 3)
4. Only Four question need to be solved.


REFERENCES:

1. Kelly Rainer, Brad Prince,Management Information Systems, Wiley
2. K.C. Laudon and J.P. Laudon, Management Information Systems: Managing the Digital Firm, 10th
Ed., Prentice Hall, 2007.
3. D. Boddy, A. Boonstra, Managing Information Systems: Strategy and Organization, Prentice Hall,
2008

Page 54

Course
Code Course Name Theory Practical Tutorial Theory Oral Tutorial Total
ILO7014 Design of
Experiments 03 -- -- 03 -- -- 03

Course Code Course Name Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment
End Sem.
Exam Test1 Test 2 Avg. of 2
Tests
ILO7014 Design of
Experiments 20 20 20 80 -- -- -- 100
Course Objectives:

Sr. No. Course Objectives:
The course aims:
1 To understand the issues and principles of Design of Experiments (DOE)
2 To list the guidelines for designing experiments
3 To become familiar with methodologies that can be used in conjunction with experimental designs for
robustness and optimization.
Course Outcomes:
Sr. No. Course Outcomes Cognitive levels of attainment as
per Bloom’s Taxonomy
On successful completion, of course, learner/student will be able to:
1 Plan data collection, to turn data into information and to make
decisions that lead to appropriate action. L6
2 Apply the methods taught to real life situations. L3
3 Plan, analyze, and interpret the results of experiments. L4, L6




Module
Detailed Contents
Hrs


01 Introduction
Strategy of Experimentation, Typical Applications of Experimental Design
Guidelines for Designing Experiments, Response Surface Methodology

06

Page 55

02 Fitting Regression Models
Linear Regression Models, Estimation of the Parameters in Linear Regression Models
Hypothesis Testing in Multiple Regression, Confidence Intervals in Multiple Regression
Prediction of new response observation, Regression model diagnostics, Testing for lack of fit


08



03 Two -Level Factorial Designs
The 22 Design, The 23 Design, The General2k Design, A Single Replicate of the 2k Design
The Addition of Center Points to the 2k Design, Blocking in the 2k Factorial Design, Split -Plot
Designs


07



04 Two -Level Fractional Factorial Designs
The One -Half Fraction of the 2k Design, The One -Quarter Fraction of the 2k Design
The General 2k-p Fractional Factorial Design, Resolution III Designs, Resolution IV and V
Designs, Fractional Factorial Split -Plot Designs


07


05 Response Surface Methods and Designs
Introduction to Response Surface Methodology, The Method of Steepest Ascent
Analysis of a Second -Order Response Surface, Experimental Designs for Fitting Response
Surfaces

07

06 Taguchi Approach
Crossed Array Designs and Signal -to-Noise Ratios, Analysis Methods, Robust design examples
04


Assessment :

Internal:
Assessment consists of two tests out of which; one should be compulsory class test and the other is either a
class test or assignment on live problems or course project.

End Semester Theory Examination:
Some guidelines for setting up the question paper. Minimum 80% syllabus should be covered in question papers
of end semester examination. In question paper weightage of each module will be proportional to number of
respective lecture hours as mention in the syllabus.
1. Question paper will comprise of total six question
2. All question carry equal marks
3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from module 3 then part (b)
will be from any module other than module 3)
4. Only Four question need to be solved.


REFERENCES:

1. Raymond H. Mayers, Douglas C. Montgomery, Christine M. Anderson -Cook, Response Surface
Methodology: Process and Product Optimization using Designed Experiment, 3rd edition,John
Wiley & Sons, New York, 2001
2. D.C. Montgomery, Design and Analysis of Experiments, 5th edition, John Wiley & Sons, New York,
2001
3. George E P Box, J Stuart Hunter, William G Hunter, Statics for Experimenters: Design,
Innovation and Discovery, 2nd Ed. Wiley
4. W J Dimond, Peactical Experiment Designs for Engineers and Scintists, John Wiley and Sons Inc.
ISBN: 0-471-39054 -2
5. Design and Analysis of Experiments (Spri nger text in Statistics), Springer by A.M. Dean, and
D. T.Voss.

Page 56

Course
Code Course Name Theory Practical Tutorial Theory Oral Tutorial Total
ILO7015 Operations
Research 03 -- -- 03 -- -- 03

Course
Code Course Name Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment
End Sem.
Exam Test1 Test 2 Avg. of 2
Tests
ILO7015 Operations
Research 20 20 20 80 -- -- -- 100
Course Objectives:

Sr. No. Course Objectives:
The course aims:
1 Formulate a real-world problem as a mathematical programming model.
2 Understand the mathematical tools that are needed to solve optimization problems
3 Use mathematical software to solve the proposed models.
Course Outcomes:
Sr. No. Course Outcomes Cognitive levels of attainment as
per Bloom’s Taxonomy
On successful completion, of course, learner/student will be able to:
1 Understand the theoretical workings of the simplex method, the
relationship between a linear program and its dual, including strong
duality and complementary slackness. L1
2 Perform sensitivity analysis to determine the direction and magnitude of
change of a model’s optimal solution as the data change. L5
3 Solve specialized linear programming problems like the transportation
and assignment problems, solve network models like the shortest path,
minimum spanning tree, and maximum flow problems. L3
4 Understand the applications of integer programming and a queuing
model and compute important performance measures
L1,L2

Page 57

Module
Detailed Contents
Hrs









01 Introduction to Operations Research : Introduction, , Structure of the
Mathematical Model, Limitations of Operations Research
Linear Programming : Introduction, Linear Programming Problem,
Requirements of LPP, Mathematical Formulation of LPP, Graphical method,
Simplex Method Penalty Cost Method or Big M-method, Two Phase Method, Revised
simplex method, Duality , Primal – Dual construction, Symmetric and Asymmetric Dual,
Weak Duality Theorem, Complimentary Slackn ess Theorem, Main Duality Theorem,
Dual Simplex Method, Sensitivity Analysis Transportation Problem : Formulation,
solution, unbalanced Transportation problem. Finding basic feasible solutions –
Northwest corner rule, least cost method and Vogel’s approxima tion method. Optimality
test: the stepping stone method and MODI method.
Assignment Problem : Introduction, Mathematical Formulation of the Problem,
Hungarian Method Algorithm, Processing of n Jobs Through Two Machines and m
Machines, Graphical Method of Two Jobs m Machines Problem Routing Problem,
Travelling Salesman Problem
Integer Programming Problem : Introduction, Types of Integer Programming Problems,
Gomory’s cutting plane Algorithm, Branch and Bound Technique.
Introduction to Decomposition algorithms.








14

02 Queuing models : queuing systems and structures, single server and multi -server
models, Poisson input, exponential service, constant rate service, finite and infinite
population
05
03 Simulation : Introduction, Methodology of Simulation, Basic Concepts, 05
Simulation Procedure, Application of Simulation Monte -Carlo Method:
Introduction, Monte -Carlo Simulation, Applications of Simulation, Advantages of
Simulation, Limitations of Simulation

04 Dynamic programming . Characteristics of dynamic programming. Dynamic
programming approach for Priority Management employment s mo o t h e n i n g ,
capital budgeting, Stagecoach/Shortest Path, cargo loading and Reliability problems.
05

05 Game Theory . Competitive games, rectangular game, saddle point, minimax
(maximin) method of optimal strategies, value of the game. Solution of games with saddle
points, dominance principle. Rectangular games without saddle point – mixed strategy for
2 X 2 games.
05
06 Inventory Models : Classical EOQ Models, EOQ Model with Price Breaks,
EOQ with Shortage, Probabilistic EOQ Model, 05

Page 58

Assessment :

Internal:
Assessment consists of two tests out of which; one should be compulsory class test and the other is either a
class test or assignment on live problems or course project.

End Semester Theory Examination:
Some guidelines for setting up the question paper. Minimum 80% syllabus should be covered in question papers
of end semester examination. In question paper weightage of each module will be proportional to number of
respective lecture hours as mention in the syllabus.
1. Question paper will comprise of total six question
2. All question carry equal marks
3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from module 3 then part (b)
will be from any module other than module 3)
4. Only Four question need to be solved.


REFERENCES:

1. Taha, H.A. "Operations Research - An Introduction", Prentice Hall, (7th Edition), 2002.
2. Ravindran, A, Phillips, D. T and Solberg, J. J. "Operations Research: Principles and Practice", John
Willey and Sons, 2nd Edition, 2009.
3. Hiller, F. S. and Liebermann, G. J. "Introduction to Operations Research", Tata McGraw Hill, 2002.
4. Oper ations Research, S. D. Sharma, KedarNath Ram Nath -Meerut.
5. Operations Research, KantiSwarup, P. K. Gupta and Man Mohan, Sultan Chand & Sons.

Page 59

Course
Code Course Name Theory Practical Tutorial Theory Oral Tutorial Total
ILO7016 Cyber Security
and Laws 03 -- -- 03 -- -- 03

Course
Code Course Name Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment
End Sem.
Exam Test1 Test 2 Avg. of 2
Tests
ILO7016 Cyber Security
and Laws 20 20 20 80 -- -- -- 100
Course Objectives:

Sr. No. Course Objectives:
The course aims:
1 To understand and identify different types of cybercrime and cyber law
2 To recognized Indian IT Act 2008 and its latest amendments
3 To learn various types of security standards compliances
Course Outcomes:
Sr. No. Course Outcomes Cognitive levels of attainment as
per Bloom’s Taxonomy
On successful completion, of course, learner/student will be able to:
1 Understand the concept of cybercrime and its effect on the outside
world. L1
2 Interpret and apply IT law in various legal issues. L5, L3
3 Distinguish different aspects of cyber law. L2, L4
4 Apply Information Security Standards compliance during software
design and development. L3, L6

Page 60

Module
Detailed Contents
Hrs

01 Introduction to Cybercrime: Cybercrime definition and origins of the world,
Cybercrime and information security, Classifications of cybercrime, Cybercrime and the
Indian ITA 2000, A global Perspective on cybercrimes.
4




02 Cyber offenses & Cybercrime: How criminal plan the attacks, Social Engg, Cyber
stalking, Cybercafé and Cybercrimes, Bot nets, Attack vector, Cloud computing,
Proliferation of Mobile and Wireless Devices, Trends in Mobility, Credit Card Frauds in
Mobile and Wireless Computing Era, Security Challenges Posed by Mobile Devices,
Registry Settings for Mobile Devices, Authentication Service Security, Attacks on
Mobile/Cell Phones, Mobile Devices: Security Implications for Organizations,
Organizational Measures for Handling Mobile, Devices -Related Security Issues,
Organizational Security Policies and Measures in Mobile
Computing Era, Laptops



9

03 Tools and Methods Used in Cyber line.
Phishing, Password Cracking, Key loggers and Spywares, Virus and Worms,
Steganography, DoS and DDoS Attacks, SQL Injection, Buffer Overflow, Attacks on
Wireless Networks, Phishing, Identity Theft (ID Theft)
6


04 The Concept of Cyberspace
E-Commerce, The Contract Aspects in Cyber Law, The Security Aspect of Cyber
Law, The Intellectual Property Aspect in Cyber Law, The Evidence Aspect in Cyber
Law, The Criminal Aspect in Cyber Law, Global Trends in Cyber Law, Legal
Framework for Electronic Data Interchange Law Relating to Electronic Bank ing,
The Need for an Indian Cyber Law

8

05 Indian IT Act.
Cyber Crime and Criminal Justice: Penalties, Adjudication and Appeals Under the IT
Act, 2000, IT Act. 2008 and its Amendments
6
06 Information Security Standard compliances
SOX, GLBA, HIPAA, ISO, FISMA, NERC, PCI. 6

Page 61

Assessment :

Internal:
Assessment consists of two tests out of which; one should be compulsory class test and the other is either a
class test or assignment on live problems or course project.

End Semester Theory Examination:
Some guidelines for setting up the question paper. Minimum 80% syllabus should be covered in question
papers of end semester examination.
In question paper weightage of each module will be proportional to number of respective lecture hours as
mention in the syllabus.
1. Question paper will comprise of total six question.
2. All question carry equal marks
3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from module 3 then part (b)
will be from any module other than mod ule 3)
4. Only Four question need to be solved.


Textbooks:

1. "Cyber Security & Cyber Laws" by Nilakshi Jain & Ramesh Menon.


REFERENCES:


1. Nina Godbole, Sunit Belapure, Cyber Security , Wiley India, New Delhi
2. The Indian Cyber Law by Suresh T. Vishwanathan; Bharat Law House New Delhi
3. The Information technology Act, 2000; Bare Act - Professional Book Publishers, New Delhi.
4. Cyber Law & Cyber Crimes By Advocate Prashant Mali; Snow White Publications, Mumbai
5. Nina Godbole, Information Systems Security, Wiley India, New Delhi
6. Kennetch J. Knapp, Cyber Security &Global Information Assurance Information Science Publishing.
7. William Stallings , Cryptography and Network Security, Pearson Publication
8. Websites for more information is available on : The Information Technology ACT, 2008 - TIFR
: https://www.tifrh.res.in
9. Website for more information , A Compliance Primer for IT professional :
https://www.sans.org/reading -room/whitepapers/compliance/compliance -primer -professionals - 33538

Page 62

Course
Code Course Name Theory Practical Tutorial Theory Oral Tutorial Total
ILO7017 Disaster
Management
and Mitigation
Measures 03 -- -- 03 -- -- 03

Course
Code Course Name Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment
End Sem.
Exam Test1 Test 2 Avg. of 2
Tests
ILO7017 Disaster
Management and
Mitigation
Measures 20 20 20 80 -- -- -- 100
Course Objectives:

Sr. No. Course Objectives:
The course aims:
1
To understand physics and various types of disaster occurring around the world
2 To identify extent and damaging capacity of a disaster
3 To study and understand the means of losses and methods to overcome /minimize it.
4 To understand role of individual and various organization during and after disaster
5 To understand application of GIS in the field of disaster management
6 To understand the emergency government response structures before, during and after
disaster
Course Outcomes:
Sr. No. Course Outcomes Cognitive levels of attainment as
per Bloom’s Taxonomy
On successful completion, of course, learner/student will be able to:
1 Get to know natural as well as manmade disaster and their extent and
possible effects on the economy L1
2 Plan of national importance structures based upon the previous history. L6
3 Get acquainted with government policies, acts and various
organizational structure associated with an emergency. L1
4 Get to know the simple do’s and don’ts in such extreme events and act
accordingly. L1

Page 63

Module
Detailed Contents
Hrs


01 Introduction
Definition of Disaster, hazard, global and Indian scenario, general perspective,
importance of study in human life, Direct and indirect effects of disasters, long term
effects of disasters. Introduction to global warming and
climate change.

03



02 Natural Disaster and Manmade disasters:
Natural Disaster: Meaning and nature of natural disaster, Flood, Flash flood, drought,
cloud burst, Earthquake, Landslides, Avalanches, Volcanic eruptions, Mudflow, Cyclone,
Storm, Storm Surge, climate change, global warming, sea level rise, ozone depletio n.
Manmade Disasters: Chemical, Industrial, Nuclear and Fire Hazards. Role of growing
population and subsequent industrialization, urbanization and changing lifestyle of
human beings in frequent occurrences of manmade
disasters.


09



03 Disaster Management, Policy and Administration
Disaster management: meaning, concept, importance, objective of disaster management
policy, disaster risks in India, Paradigm shift in disaster management.
Policy and administration:
Importance and principles of disast er management policies, command and co -ordination
of in disaster management, rescue operations -how to start with
and how to proceed in due course of time, study of flowchart showing the entire process.


06


04 Institutional Framework for Disaster Management in India:
Importance of public awareness, Preparation and execution of emergency management
programme. Scope and responsibilities of National Institute of Disaster Management
(NIDM) and National disaster management authority
(NDMA) in India. Met hods and measures to avoid disasters , Management of casualties, set
up of emergency facilities, importance of effective communication amongst
different agencies in such situations. Use of Internet and softwares for effective
disaster management. Applications of GIS, Remote sensing and GPS in this regard.

06


05 Financing Relief Measures:
Ways to raise finance for relief expenditure, role of government agencies and NGO’s in
this process, Legal aspects related to finance raising as well as overall management of
disasters. Various NGO’s and the works they have carried out in the past on the occurrence
of various disasters, Ways to approach these teams. International relief aid agencies and
their role in extreme events.

09




06 Preventive and Mitigation Measures:
Pre-disaster, during disaster and post -disaster measures in some events in general
Structural mapping: Risk mapping, assessment and analysis, sea walls and embankments,
Bio shield, shelters, early warning and communication
Non-Structural Mitigation: Community based disaster preparedness, risk transfer and risk
financing, capacity develop ment and training, awareness and education, contingency
plans.
Do’s and don’ts in case of disasters and effective implementation of relief aids.



06

Page 64

Assessment :

Internal:
Assessment consists of two tests out of which; one should be compulsory class test and the other is either a
class test or assignment on live problems or course project.

End Semester Theory Examination:
Some guidelines for setting up the question paper. Minimum 80% syllabus should be covered in question papers
of end semester examination. In question paper weightage of each module will be proportional to number of
respective lecture hours as mention in the syllabus.
1. Question paper will comprise of total six question
2. All question carry equal marks
3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from module 3 then part (b)
will be from any module other than module 3)
4. Only Four question need to be solved.

REFERENCES:

1. ‘Disaster Management’ by Harsh K.Gupta, Universities Press Publications.
2. ‘Disaster Management: An Appraisal of Institutional Mechanisms in India’ by O.S.Dagur, published by
Centre for land warfare studies, New Delhi, 2011.
3. ‘Introduction to International Disaster Management’ by Damon Copolla, Butterworth Heinemann
Elseveir Publi cations.
4. ‘Disaster Management Handbook’ by Jack Pinkowski, CRC Press Taylor and Francis group.
5. ‘Disaster management & rehabilitation’ by Rajdeep Dasgupta, Mittal Publications, New Delhi.
6. ‘Natural Hazards and Disaster Management, Vulnerability and Mitigatio n – R B Singh, Rawat
Publications
7. Concepts and Techniques of GIS –C.P.Lo Albert, K.W. Yonng – Prentice Hall (India) Publications.
(Learners are expected to refer reports published at national and International level and updated
information available on aut hentic web sites)

Page 65

Course
Code Course Name Theory Practical Tutorial Theory Oral Tutorial Total
ILO7018 Energy Audit
and
Management 03 -- -- 03 -- -- 03

Course
Code Course Name Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment
End Sem.
Exam Test1 Test 2 Avg. of 2
Tests
ILO7018 Energy Audit and
Management 20 20 20 80 -- -- -- 100
Course Objectives:

Sr. No. Course Objectives:
The course aims:
1
To understand the importance of energy security for sustainable development and the fundamentals of
energy conservation
2 To introduce performance evaluation criteria of various electrical and thermal installations
to facilitate energy management.
3 To relate the data collected during performance evaluation of systems for identification of
energy saving opportunities.
Course Outcomes:
Sr. No. Course Outcomes Cognitive levels of attainment as per
Bloom’s Taxonomy
On successful completion, of course, learner/student will be able to:
1 To identify and describe present state of energy security and its
importance L1, L2, L4
2 To identify and describe the basic principles and
methodologies adopted in energy audit of a utility. L1, L2, L4
3 To describe the energy performance evaluation of
some common electrical installations and identify
the energy saving opportunities. L1, L2, L4
4 To describe the energy performance evaluation of
some common thermal installations and identify
the energy saving opportunities. L1, L2, L4
5 To analyze the data collected during performance evaluation and
recommend energy saving measures L4

Page 66

Module
Detailed Contents
Hrs


01 Energy Scenario:
Present Energy Scenario, Energy Pricing, Energy Sector Reforms, Energy Security,
Energy Conservation and its Importance, Energy Conservation Act- 2001 and its Features.
Basics of Energy and its various forms, Material and
Energy balance

04



02 Energy Audit Principles:
Definition, Energy audit - need, Types of energy audit, Energy management (audit)
approach -understanding energy costs, Bench marking, Energy performance, Matching
energy use to requirement, maximizing system efficiencies, Optimiz ing the input energy
requirements, Fuel and energy substitution. Elements of monitoring& targeting; Energy
audit Instruments; Data and information -analysis.
Financial analysis techniques: Simple payback period, NPV, Return on investment (ROI),
Internal rate of return (IRR)


08



03 Energy Management and Energy Conservation in Electrical System: Electricity
billing, Electrical load management and maximum demand Control; Power factor
improvement, Energy efficient equipment and appliances, star ratings.
Energy efficiency measures in lighting system, Lighting control: Occupancy sensors,
daylight integration, and use of intelligent controllers.
Energy conservation opportunities in: water pumps, industrial drives, induction motors,
motor retrofitting, soft starters, variable speed drives.


10



04 Energy Management and Energy Conservation in Thermal Systems:
Review of different thermal loads; Energy conservation opportunities in: Steam
distribution system, Assessment of steam distribution losses, Steam leakages, Steam
trapping, Condensate and flash steam recovery system.
General fuel economy measures in Boilers and furnaces, Waste heat recovery, use of
insulation - types and application. HVAC system: Coefficient of performance, Capacity,
factors affecting Refrigeration and Air Conditioning system performance and savings
opportunities.


10

05 Energy Performance Assessment:
On site Performance evaluation techniques, Case studies based on: Motors and variable
speed drive, pumps, HVAC system calculations; Lighting System:
Installed Load Efficacy Ratio (ILER) method, Financial Analysis.
04

06 Energy conservation in Buildings:
Energy Conservation Building Codes (ECBC): Green Building, LEED rating,
Application of Non -Conventional and Renewable Energy Sources
03

Page 67

Assessment :

Internal:
Assessment consists of two tests out of which; one should be compulsory class test and the other is either a
class test or assignment on live problems or course project.

End Semester Theory Examination:
Some guidelines for setting up the question paper. Minimum 80% syllabus should be covered in question papers
of end semester examination. In question paper weightage of each module will be proportional to number of
respective lecture hours as mention in the syllabus.
1. Question paper will comprise of total six question
2. All question carry equal marks
3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from module 3 then part (b)
will be from any module other than module 3)
4. Only Four question need to be solved.


REFERENCES:

1. Handbook of Electrical Installation Practice, Geofry Stokes, Blackwell Science
2. Designing with light: Lighting Handbook, By Anil Valia, Lighting System
3. Energy Management Handbook, By W.C. Turner, John Wiley and Sons
4. Handbook on Energy Audits and Management, edited by A. K. Tyagi, Tata Energy
Research Institute (TERI).
5. Energy Management Principles, C.B.Smith, Pergamon Press
6. Energy Conservation Guidebook, Dale R. Patrick, S. Fardo, Ray E. Richardson, Fair mont Press
7. Handbook of Energy Audits, Albert Thumann, W. J. Younger, T. Niehus, CRC Press
8. www.energymanagertraining.com
9. www.bee -india.nic.in .

Page 68

Course
Code Course Name Theory Practical Tutorial Theory Oral Tutorial Total
ILO7019 Development
Engineering 03 -- -- 03 -- -- 03

Course
Code Course Name Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment
End Sem.
Exam Test1 Test 2 Avg. of 2
Tests
ILO7019 Development
Engineering 20 20 20 80 -- -- -- 100
Course Objectives:

Sr. No. Course Objectives:
The course aims:
1 To familiarise the characteristics of rural Society and the Scope, Nature and Constraints of rural
Development
2 To provide an exposure to implications of 73rdCAA on Planning, Development and Governance
of Rural Areas
3 An exploration of human values, which go into making a ‘good’ human being, a ‘good’
professional, a ‘good’ society and a ‘good life’ in the context of work life and the personal life of
modern Indian professionals
4 To familiarise the Nature and Type of Human Values relevant to Planning Institutions
Course Outcomes:
Sr. No. Course Outcomes Cognitive levels of attainment as per
Bloom’s Taxonomy
On successful completion, of course, learner/student will be able to:
1 Demonstrate understanding of knowledge for Rural Development. L3
2 Prepare solutions for Management Issues. L3
3 Take up Initiatives and design Strategies to complete the task L6
4 Develop acumen for higher education and research. L6
5 Demonstrate the art of working in group of different nature L3
6 Develop confidence to take up rural project activities
independently.
L6

Page 69

Module Contents Hrs
1 Introduction to Rural Development Meaning, nature and scope of development; Nature of
rural society in India; Hierarchy of settlements; Social, economic and ecological constraints
for rural development
Roots of Rural Development in India Rural reconstruction and Sarvodaya program before
independence; Impact of volunta ry effort and Sarvodaya Movement on rural development;
Constitutional direction, directive principles; Panchayati Raj - beginning of planning and
community development; National extension services. 08
2 Post-Independence rural Development Balwant Rai Mehta Committee - three tier system
of rural local Government; Need and scope for people’s participation and Panchayati Raj;
Ashok Mehta Committee - linkage between Panchayati Raj, participation and rural
development. 06
3 Rural Development Initiatives in Five Year Plans Five Year Plans and Rural Development;
Planning process at National, State, Regional and District levels; Planning, development,
implementing and monitoring organizations and agencies; Urban and rural interface -
integrated approach and lo cal plans; Development initiatives and their convergence; Special
component plan and sub -plan for the weaker section; Micro -eco zones; Data base for local
planning; Need for decentralized planning; Sustainable rural development 07
4 Post 73rd Amendment Scenario 73rd Constitution Amendment Act, including - XI
schedule, devolution of powers, functions and finance; Panchayati Raj institutions
- organizational linkages; Recent changes in rural local planning; Gram Sabha - revitalized
Panchayati Raj; Institut ionalization; resource mapping, resource mobilization including
social mobilization; Information Technology and rural planning; Need for further
amendments. 04
5 Values and Science and Technology Material development and its values; the
challenge of science and technology; Values in planning profession, research and education
Types of Values Psychological values — integrated personality; mental health; Societal
values — the modern search for a good society; justice, democracy, rule of law, values in
the Indian constitution; Aesthetic values — perception and enjoyment of beauty; Moral and
ethical values; nature of moral judgment; Spiritual values; different concepts; secular
spirituality; Relative and absolute values; Human values — humanism and human v alues;
human rights; human values as freedom, creativity, love and wisdom 10
6 Ethics Canons of ethics; ethics of virtue; ethics of duty; ethics of responsibility.
Work ethics; Professional ethics; Ethics in planning profession, research and education 04

Page 70

Assessment :

Internal Assessment for 20 marks:
Consisting of Two Compulsory Class Tests
First test based on approximately 40% of contents and second test based on remaining contents
(approximately 40% but excluding contents covered in Test I)

End Semester Examination:
The weightage of each module in end semester examination will be proportional to number of
respective lecture hours mentioned in the curriculum.
1. Question paper will comprise of total six question
2. All question carry equal marks
3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from module 3 then
part (b) will be from any module other than module 3)
4. Only Four question need to be solved.

Reference
1. ITPI, Village Planning and Rural Development, ITPI, New Delhi
2. Thooyavan, K.R. Human Settlements: A 2005 MA Publication, Chennai
3. GoI, Constitution (73rdGoI, New Delhi Amendment) Act, GoI, New Delhi
4. Planning Commission, Five Year Plans, Planning Commission
5. Planning Commission, Manual of Integrated District Planning, 2006, Planning Commission New
Delhi
6. Planning Guide to Beginners
7. Weaver, R.C., The Urban Complex, Doubleday
8. Farmer, W.P. et al, Ethics in Planning, American Planning Association, Washington.
9. How, E., Normative Ethics in Planning, Journal of Planning Literature, Vol.5, No.2, pp. 123-150
10. Watson, V. Conflicting Rationalities: -- Implications for Planning Theory and Ethics, Planning
Theory and Practice, Vol. 4, No.4, pp.395 – 407

Page 71

Subject
Code Subject Name Teaching Scheme
(Contact Hours)
Credits Assigned
Theory Practical Tutorial Theory Oral Tutorial Total
IoTCSBCL
701 ML &
Blockchain Lab
-- 2 -- -- 2 -- 2

Subject
Code Subject Name Examination Scheme
Theory Marks
Term Work Oral Total Internal assessment End Sem.
Exam Test1 Test 2 Avg. of
2 Tests
IoTCSBCL
701 ML &
Blockchain Lab
-- -- -- -- 25 25 50

Lab Objectives:
Sr. No. Lab Objectives
The course aims:
1 To introduce the basic concepts of tools and techniques of Machine Learning.
2 To acquire in -depth understanding of various supervised and unsupervised machine learning
algorithms.
3 To be able to apply various ensemble techniques for combining Machine Learning models and also
demonstrate dimensionality reduction techniques.
4 To be a ble to understand fundamental of blockchain technology.
5 To be able to apply understanding of consensus algorithms and smart contract programming.
6 To be able to collate blockchain based solutions towards various industry -based application.

Lab Outcomes:
Sr. No. Lab Outcomes Cognitive levels of
attainment as per
Bloom’s Taxonomy
On successful completion, of course, learner/student will be able to:
1 To interpret and conceptualize the basic concepts of tools and techniques of
Machine Learning. L2
2 To demonstrate machine learning algorithms with complex datasets L3
3 To understand fundamental neural network architecture and concepts. L2
4 To examine fundamental concepts of block chain technology and consensus
algorithm L4
5 To develop smart contracts L6
6 To collate blockchain based solutions towards various industry -based
application. L6

Prerequisite: Must have completed the course on Introduction to Linear Algebra and have basic fami liarity with
probability theory and basics of programming language.

Page 72

Sr. No. Suggested list of Assignments LO
1 To implement Supervised Learning using Linear regression algorithm LO1
2 To implement Supervised Learning using Logistic regression algorithm LO1
3 To implement PCA / SVD / LDA LO2
4 To implement Decision Tree Algorithms LO2
5 To implement Graph based clustering and CART algorithm LO2
6 To implement a Simple Neural Network using backpropogation . LO3
7 To study installation tools and basic blockchain concepts. LO4
8 To implement Smart contracts using Solidity/Python/ Java language. LO5
9 To implement Smart contracts using Solidity/Python/ Java language. LO5
10 To design and implement Mini -project on Machine Learning / Blockchain topics LO6

Text Books:
1. Shai Shalev -Shwartz; Shai Ben -David, MACHINE LEARNING From Theory to Algorithms, Cambridge University
Press, 2014
2. Sebastian Raschka; Yuxi (Hayden) Liu, Vahid Mirjalili, Machine Learning with PyTorch and Scikit -Learn, PackT,
2022
3. Bikramaditya Singhal, Gautam Dhameja, Priyansu Sekhar Panda, Beginning Blockchain A Beginner's Guide to
Building Blockchain Solutions, Apress, 2018
4. Sandeep Kumar Panda, Vaibhav Mishra, Sujata Priyambada Dash, Ashis Kumar Pani, Recent Advances in
Blockchain Technology Real -World Applications, Springer, 2023
5. Artificial Intelligence and Data Mining Approaches in Security Frameworks Editor(s):Neeraj Bhargava, Ritu
Bhargava, Pramod Singh Rath ore, Rashmi Agrawal, 2021.
References:
1. Sebastian Raschka, Vahid Mirjalili Python Machine Learning, 3rd Edition, 2019, Packt
2. Machine Learning: A Probabilistic Perspective, Kevin P Murphy, MIT Press.
3. Christopher M. Bishop. Pattern Recognition and Machine Lea rning. Springer 2006.
4. Tom Mitchell. Machine Learning. McGraw Hill, 1997.
5. Arjuna Sky Kok, Hands -on Blockchain for Python Developers, 2019, Packt
Online References and MOOC Courses :
1. https://www.toptal.com/ethereum/one -click -login -flows -a-metamask -tutorial
2. What Is Machine Learning in Security? - Cisco
3. https://www.mdsny.com/5 -top-machine -learning -use-cases -for-security/
4. https://trufflesuite.com/docs/truffle/how -to/truffle -with-metamask/
5. https://remix -ide.readthedocs.io/en/latest/index.html
6. https://nptel.ac.in/courses/106/106/106106139/
7. https://nptel.ac.in/courses/106/106/106106202/
8. https://www.classcentral.com/course/independent -machine -learning -security -12651
Assessment:
Term Work: Term Work shall consist of at least 10 practicals based on the above list. Also Term work Journal must
include at least 2 assignments.
Term Work Marks: 25 Marks (Total marks) = 15 Marks (Experiment) + 5 Marks (Assign ments) + 5 Marks (Attendance)
Oral Exam: An Oral exam will be held based on the above syllabus.

Page 73

Subject Code
Subject Name
Teaching Scheme (Contact
Hours)
Credits Assigned
Theory Practical Tutorial Theory Oral Tutorial Total
IoTCSBCL702 Edge and Fog
Computing Lab
-- 2 -- -- 1 -- 1

Subject Code Subject Name Examination Scheme
Theory Marks
Term
Work Oral Total Internal assessment End
Sem.
Exam Test1 Test 2 Avg. of 2
Tests
IoTCSBCL7
02 Edge and Fog
Computing Lab
-- -- -- -- 25 25 50

Lab Objectives:
Sr. No. Lab Objectives
1 To study the concepts of virtual servers and AWS Edge platforms
2 To get acquainted with different Aws IoT Core Services.
3 To learn message passing between AWS IoT Core devices
4 To study different simulators and development of Edge Computing networks
5 To study different simulators and development of FogComputing networks

Lab Outcomes:
Sr. No. Lab Outcomes Cognitive Levels
of Attainment as
per Bloom’s
Taxonomy
On successful completion of the course students will be able to,
1 Understand the concept of virtual servers deployed on AWS Edge platform L1
2 Analyze the use of AWS IoT Core and related services. L3
3 To examine the message passing techniques in AWS IoT Core devices and a ssess
the security using VPC on AWS. L3
4 Deploy Edge computing networks using Edge computing simulators L4
5 Deploy Fog computing networks using Fog computing simulators L5

Page 74

Prerequisite: Cloud Computing and IoT concepts

Sr. No. Suggested list of Assignments LO
1 Create and deploy virtual servers on AWS / Azure. LO1
2 To deploy Raspberry Pi on AWS IoT Core LO2
3 To implement MQTT messaging between Raspberry Pi and AWS IoT Core LO2
4 To implement virtual private cloud (VPC) on AWS for IoT services. LO3
5 Study assignment on Edge and Fog Simulators LO4
6 Design and deploy an edge computing architecture using edge simulators such as
Mobius / EdgeCloudSim. LO4
7 Develop and evaluate edge -based data analytics algorithms in an edge simulator. LO5
8 Design and deploy a fog computing architecture using simulators such as iFogSim
/ CloudSim. LO4
9 Explore collaboration between edge and fog nodes for IoT applications. LO5



Text Books:
1. “Fog and Edge Computing ” by Rajkumar Buyya, Satish Narayana Srirama, Wiley Publications
2. "Edge Computing: Models, Technologies, and Applications" by Mung Chiang, Bharath
Balasubramanian, and H. Vincent Poor.
3. Edge Computing with Python: End -to-end Edge Applications, Python Tools and Techniques, Edge
Architectures, and AI Benefit” by Abhinandan Bhadauria, BPB publications .
4. “Edge Computing: Simply in Depth” by Ajit Singh,
5. Edge Computing: Fundamentals, Advances a nd Applications (Advances in Industry 4.0 and Machine
Learning) by K. Anitha Kumari, G. Sudha Sadasivam, D. Dharani, M. Niranjanamurthy , CRC Press.


References:

1. "Edge Computing for IoT: Architectures and Applications" by Bharat Bhargava, Sudip Misra, Val entina
E. Balas, and Raghvendra Kumar
2. "Practical Industrial Internet of Things Security: A practitioner's guide to securing connected industries"
by Sravani Bhattacharjee and Rajdeep Chowdhury
3. "Edge Computing: An Introduction to the Next Generation of Networked Systems" by Kiran Chitturi,
Bharadwaj Veeravalli, and Satish Narayana Srirama
4. "Building the Web of Things: With examples in Node.js and Raspberry Pi" by Dominique D. Guinard
and Vlad M. T rifa
5. "Internet of Things (IoT): Technologies, Applications, Challenges, and Solutions" edited by
Balamuralidhar P., Bharadwaj Veeravalli, and V. Raghu
6. "Fog and Edge Computing: Principles and Paradigms" by Rajkumar Buyya, Satish Srirama, and Pradeep
Kumar S .

Page 75

7. "IoT Fundamentals: Networking Technologies, Protocols, and Use Cases for the Internet of Things" by
David Hanes and Gonzalo Salgueiro
8. "Edge Analytics in IoT" by Shivashankar B. Nair, Siddhartha Bhattacharyya, and Thomas Edward
Joshua
9. "Edge Computing: The Convergence of Big Data and Internet of Things" by Samee U. Khan, Albert Y.
Zomaya, and Salman A. Baset


Online References:

1. http://www.steves -internet -guide.com/mqtt -protocol -messages -overview/
2. https://aws.amazon.com/iot -core/
3. https://github.com/CagataySonmez/EdgeCloudSim/wiki
4. https://www.cloudsimtutorials.online/ifogsim -project -structure -a-beginners -guide/
5. https://www.udemy.com/course/essential -ifogsim -tutorials/
6. https://slogix.in/source -code/ifog -computing -samples/how -to-create -fog-topology -in-ifogsim/


Assessment:

Term Work: Term Work shall consist of at least 10 to 12 practicals based on the above list. Also, Term
work Journal must include at least 2 assignmen ts.
Term Work Marks: 25 Marks (Total marks) = 15 Marks (Experiment) + 5 Marks (Assignments) + 5 Marks
(Attendance)
Oral Exam: An Oral exam will be held based on the above syllabus / suggested list of Assignment .

Page 76

Subject
Code Subject Name Theory Practical Tutorial Theory Practical &
Oral Tutorial Total
IoTCSBC
L703 DevSecOps
Lab -- 2 -- -- -- -- 01

Subject
Code Subject Name Examination Scheme
Theory Marks
Term
Work Practical &
Oral Total Internal assessment End
Sem.
Exam Test1 Test 2 Avg. of 2
Tests
IoTCSBCL
703 DevSecOps
Lab -- -- -- -- 25 25 50

Lab Objectives:
Sr. No. Lab Objectives
1 To understand the concept of distributed version control.
2 To familiarize with Jenkins build & test software Applications & Continuous integration.
3 To understand Docker to build, ship and run containerized images.
4 To familiarize with the concept of Software Configuration Management with Continuous
Monitoring.
5 To understand the basics of Application/code security testing and threat modeling.
6 To familiarize with the concept of Cloud and Infrastructure as a Code.

Lab Outcomes:
Sr. No. Lab Outcomes Cognitive Levels of
Attainment as per
Bloom’s Taxonomy
On successful completion of the course students will be able to,
1 Understand the concepts of distributed version control using GIT and
GITHUB L1

Page 77

2 Apply Jenkins to Build, Deploy and Test the Software Applications L3
3 Analyze & Illustrate the Containerization of OS images and deployment of
applications over Docker L3,L4
4 Deploy and Examine the Software Configuration management using
Ansible and Continuous monitoring and alerting using Prometheus and
Nagios L4
5 Use Sonarqube and snyk to perform code quality checks and Threat Dragon
to create threat models to identify threats in the system. L3
6 Implement Terraform scripts to manage VMs on a cloud. L3

Sr.
No. Module Detailed Content Hours LO
Prerequisite Concept of DevOps with related technologies which are
used to Code, Build, Test, Configure & Monitor the
Software Applications. 02 -
I Version Control
using GIT To Perform Version Control on documents/files websites/
Softwares using GIT & GITHUB that covers all GIT
commands given in GIT cheat sheet
● To implement Version control for different
files/directories using GIT
● To implement version control using GITHUB to
sync local GIT repositories and perform various related
operations. 04 LO 1
II Working with
Jenkins
● To deploy and test Java/web/Python application
on jenkins server
● To implement Jenkins pipeline using
scripted/declarative pipeline
● To use jenkins to deploy and run test cases for
Java/Web application using Selenium/JUnit 04 LO 2
III Containerization
● To use docker to run containers of different
applications and operating Systems
● To create a custom docker image using Dockerfile
and upload it to the docker hub. 04 LO 3
IV
Software
Configuration
Management and
Continuous
Monitoring
● To implement continuous deployment using
Ansible
● To Implement automated monitoring and alerting
using Prometheus
● To implement continuous monitoring using
Splunk/NagiOS 04 LO 4

Page 78

V Application/Code
Security ● To implement Application and code security
testing using snyk
● To implement Static Application Security Testing
using SonarQube
● To implement threat models to identify threats in
the system using Threat Dragon 04 LO 5
VI Cloud and
Infrastructure as a
code ● To create and work with virtual machine on cloud
(GCP / AWS / Azure)
● To implement terraform script for deploying
compute/Storage/network infrastructure on the public
cloud platform (GCP / AWS / Azure) 04 LO 6

Text Books:
1. Prem Kumar Ponuthorai, Jon Loeliger, Version Control with Git, 3rd Edition,O'Reilly Media.
2. John Ferguson Smart,”Jenkins, The Definitive Guide”, O'Reilly Publication.
3. Karl Matthias & Sean P. Kane, Docker: Up and Running, O'Reilly Publication.
4. Russ McKendrick , Learn Ansible, Pakt Publication.
5. Yevgeniy Brikman, Terraform: Up and Running, 3rd Edition, O'Reilly Publication.
6. G. Ann Campbell ,SonarQube in Action,First Edition, Manning publication.
References:
1. Sanjeev Sharma and Bernie Coyne,”DevOps for D ummies”, Wiley Publication
2. Httermann, Michael, “DevOps for Developers”,Apress Publication.
3. Joakim Verona, “Practical DevOps”,Pack publication
Online references:
Sr.
No. Topic Link
1 GIT Cheat sheet https://www.atlassian.com/git/tutorials/atlassian -git-cheatsheet
2 Jenkins 1) https://www.javacodegeeks.com/2021/04/how -to-create -run-a-
job-in-jenkins -using -jenkins -freestyle -project.html
2) https://k21academy.com/devops -foundation/ci -cd-pipeline -
using -jenkins/

3 Docker https://docs.docker.com/get -started/docker_cheatsheet.pdf
4 Ansible https://docs.ansible.com/ansible/latest/index.html
5 Prometheus https://prometheus.io/docs/introduction/overview/
6 Snyk https://snyk.io/learn/application -security/static -application -security -
testing/

Page 79

7 Threatdragon https://www.threatdragon.com/#/
8 SonarQube https://docs.sonarqube.org/latest/
9 Terraform https://developer.hashicorp.com/terraform/intro

Assessment
Term Work: Term Work shall consist of at least 10 to 12 practicals based on the above list. Also Term work Journal must
include at least 2 assignments.
Term Work Marks: 25 Marks (Total marks) = 15 Marks (Experiment) + 5 Marks (Assignments) + 5 Marks (Atte ndance)
Oral Exam: An Oral exam will be held based on the above syllabus

Page 80

Course Code Course Name Theory Practical Tutorial Theory Practical
/Oral Tutorial Total
IoTCSBCL70
4 Open -Source Intelligence
(OSINT) Lab -- 02 -- -- 1 -- 01


Course
Code
Course Name Theory Marks
Term
Work
Practical/Oral
Total Internal assessment End Sem.
Exam Test1 Test 2 Avg. of 2
Tests
IoTCSBCL70
4 Open -Source Intelligence
(OSINT)
Lab
--
--
--
--
25
25
50

Lab Objectives:
Sr.
No. Lab Objectives
The course aims:
1 To provide hands -on experiences for students to develop critical thinking, research skills
2 To incorporate ethical usage of OSINT tools.
3 To get familiar with OSINT framework and its usage on publicly available data.
4 To learn to use the OSINT tools for Social Media, Email, Image, or network analysis, websites and understand the
usage for Digital Forensics .
5 To performs background/profile/corporate profile checks, corporate Open -Source Intelligence (OSINT) Assessment
etc.
6 Identify intelligence needs and leverage a broad range of tools and sources to improve data collection, analysis, and
decision making.


Lab Outcomes:
Sr. No. Lab Outcomes Cognitive levels of
attainment as per
Bloom’s Taxonomy
On successful completion, of course, learner/student will be able to:
1 Gain knowledge about Open -Source Intelligence understand the threats and
think critically about countermeasures. L1, L2, L3
2 Conduct advanced searches to gather intelligence and apply advance OSINT
search techniques and tools. L1, L2, L4
3 Use OSINT tools for analysis fake news, image, video data L1, L2, L3
4 Conduct advanced searches to gather intelligence from social media sites and
understand the use of Public Records for corporate and business intelligence
etc. L1, L2
5 Gather information/metadata about Maps to performance detailed map profiling L1, L2, L3
6 Get familiar with Technical Foot printing websites for mitigating various
threats L1, L2


Prerequisite:

Page 81

1. Kali Linux Installation and VM deployment.
2. Networking and security fundamentals

DETAILED SYLLABUS:

Sr.
No. Module Detailed Content Hours LO
Mapping
0 The Evolution of Open -
Source Intelligence,
Open -Source Information Categories OSINT Types, Digital
Data Volume, OSINT Organizations, Parties Interested in
OSINT Information, International Organizations, Information
Gathering Types, Benefits of OSINT, Challenges of Open -
Source Intelligence Legal and Ethical Constraints 1 LO1
I Introduction To Online
Threats and
Countermeasures
Online Threats -.
Securing the Operating System: Hardening the Windows OS,
Staying Private in Windows, Destroying Digital Traces
General Privacy Settings - Avoiding Pirated Software, Handling
Digital Files Metadata, Physically Securing Computing Devices 1 LO1
II Using Search Engines
to Locate Information Search Engine Technique - Keywords Discovery and Research,
- Google, Privacy -Oriented Search Engines, Other Search
Engines, Business Search Sites, Metadata Search Engines, Code
Search FTP Search Engines
Automated Search Tools, Dorks 2 LO2
III Searching for Digital
Files News Search - Customize Google News, News Websites, Fake
News Detection
- Document Search, Image, Video, File Extension and File
Signature List, Productivity Tools 2 LO4
IV People Search Engines
and Public Records
Social Media Intelligence:
What Is Social Media Intelligence? Social Media Content Types,
General Resources for Locating Information on Social Media
Sites
Pastebin Sites

People Search Engine, Public Records and example of Public
Records, Searching for Personal Details, General People Search ,
Online Registries, Vital Records, Criminal and Court Search,
Property Records, Tax and Financial Records, Social Security
Number Search
Username Check, E -mail Search and Investigation Data
Compromised Repository Websites, Phone Number Search 6 LO4
V Online Maps: The Basics of Geolocation Tracking, How to Find the GPS
Coordinates of Any Location on a Map
How to Find the Geocode Coordinates from a Mailing Address,
General Geospatial Research Tools Commercial Satellites,
Date/Time Around the World, Location -Based social media,
Conducting Location Searches on social media Using Automated
Tools, Country Profile Information Tr ansport Tracking 6 LO5
VI Technical Foot
printing:
Website History and Website Capture
Website Monitoring Services - RSS Feed

Investigate the Target Website, Investigate the Robots.txt File,
Mirror the Target Website Extract the Links Check the Target 6 LO6

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Website’s Backlinks Monitor Website Updates Check the
Website’s Archived Contents

Identify the Technologies Used, Web Scraping T ools
Investigate the Target Website’s File Metadata, Website
Certification Search, Website Statistics and Analytics Tools,
Website Reputation Checker Tools, Passive Technical
Reconnaissance Activities, WHOIS Lookup, Subdomain
Discovery, DNS Reconnaissance , IP Address Tracking


Textbooks:
1. Open Source Intelligence Methods and Tools: A Practical Guide to Online Intelligence by Nihad A. Hassan (Author),
Rami Hijazi (Author)
2. OSINT Techniques - Resources for Uncovering Online Information - 10th Edition (2023) by Michael Bazzell
3. Operator Hand book: Red Team + OSINT + Blue Team Reference by Joshua Picolet

References:
1. We Are Bellingcat: Global Crime, Online Sleuths, and the Bold Future of News by Eliot Higgins
2. Extreme Privacy: What It Takes to Disappear in America by Michael Bazzell
Tools:
● https://cheatsheet.haax.fr/open -source -intelligence -osint/
● https://inteltechniques.com/tools/
● https://hunter.io/
● https://www.shodan.io/
https://github.com/laramies/theHarvester
● https://www.osintcombine.com/osint -bookmarks
● https://osintframework. com/
● https://learn.baselgovernance.org/enrol/index.php?id=79
● https://inteltechniques.com/
● https://www.bellingcat.com//
● https://www.tracelabs.org/

List of Experiments/Mini -Project.
Sr.
No. Detailed Content
1. . Perform Email Header Analysis for extracting valuable information like sender IP address, email
servers, and routing information.
. Conduct email address enumeration by attempting to verify the existence of email addresses within a
target domain. Use tools like the Harvester or thehunter.io to search for email addresses associated with a
specific domain. This can help identify valid email addresses within an organization.
. Analyze the metadata of an email, including date and time stamps, email clients u sed, or the originating
IP address, email's origin, potential geographic location of the sender, or possible email routing
2 Using OSINT tool such as (Harverster) you can gather information like emails, subdomains, hosts, employee
names, open ports and banners from different public sources like search engines, PGP key server.
3 Use OSINT DORKS (create and execute search queries) to verify the accuracy of the information by cross -
referencing various sources and critically evaluating the reliability and c redibility of the New article.

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4 To perform the reverse Image analysis for finding physical location where the content was captured. Use OSINT
tool to use image metadata, landmarks, street signs, or other visual cues to identify the geolocation accurately.
5 Using OSINT tools gather Tactical information using WHOIS lookup tools or websites like DomainTools
(domain, registration details, owner's contact information, registration date, and expiration date.) Archives, Text,
Reverse Image Search, Images and EXIF data, Source code, Others TLD, Mentions of target, Check info such as
via RSS,SSL certificates, Rob ots/Sitemap, Port scans, Reverse IP lookup
6 Utilize website crawling OSINT tools to gather a comprehensive list of URLs, internal links, and structure of the
website
7 Use OSINT Tools to identify the technologies and frameworks used by the website, such as content management
systems (CMS), server software, programming languages, or analytics tools and create vulnerability reports.

8 Determine the geolocation (country, city, or approximate location) of each IP address (at least 10) One can use
online IP geolocation tools, databases, and various techniques to gather information and accurately identify the
physical location associated with each IP
9 Conduct a comprehensive OSINT investigation about well -known company and gather information about the
company's history, key executives, financial data, partnerships, news mentions, and any other relevant details
using online databases, news articles, corporate websites, and industry reports
10 Analyze the company's competitors to understand their market positioning, strengths, and weaknesses. Tools like
SEMrush, Similar Web, or Alexa or any other OSINT tool can provide website traffic, keyword analysis, and
competitor comparisons
11 Fake News detection - Analyze at least 5 OSINT tools to detect, verify, authenticate, fake news and report.
12. Example Mini Project suggestion -
Digital Footprint Analysis using OSINT Tools:
Assess and analyze your own digital footprints wrt, Personal Information, data (full name, age, date of birth,
address, phone number, and email address), images, videos (online directories, social media profiles (at least 3
social media accounts), personal websites, Online Professional Presence and analyze
1.Posts, comments, photos, and other content that they have shared publicly or w ith specific privacy settings
2.Analyze their online interactions, connections, interests, and activities.
3. Analyze the nature of the content, locations, events, or people, as it can provide insights into activities,
hobbies, or relationships.
4. Analyze work experience, educational background, skills, recommendations, and any professional
associations or achievements.

Page 84

Course
Code Course Name Teaching Scheme (Contact
Hours)
Credits Assigned
Theory Practical Tutorial Theory Oral Tutorial Total
IoTCSBCP7
01 Major Project I -- 6# -- -- 3 -- 3


Subject
Code Subject Name Examination Scheme
Theory Marks
Term
Work Practical &
Oral Total Internal assessment End
Sem.
Exam Test1 Test 2 Avg. of 2
Tests
IoTCSBCP
701 Major Project
1 -- -- -- -- 25 25 50


Course Objectives:
The project work facilitates the students to develop and prove Technical, Professional and Ethical skills and
knowledge gained during graduation program by applying them from problem identification, analyzing the
problem and designing solutions.
Course Outcomes: Learner will able
1 To develop the understanding of the problem domain through extensive review of
literature.
2 To Identify and analyze the problem in detail to define its scope with problem specific data.
3 To know various techniques to be implemented for the selected problem and related
technical skills through feasibility analysis.
4 To design solutions for real -time problems that will positively impact society and
environment.
5 To develop clarity of presentation based on communication, teamwork and leadership skills.
6 To inculcate professional and ethical behavior.

Guidelines:

• Project Topic Selection and Allocation:
1. Project topic selection Process to be defined and followed:
2. Project orientation can be given at the end of sixth semester.
3. Students should be informed about the domain and domain experts whose guidance can be taken before
selecting projects.
4. Students should be recommended to refer papers from reputed conferences/ journals like IEEE, Elsevier,

Page 85

ACM etc. which are not more than 3 years old for review of literature.
5. Students can certainly take ideas from anywhere but be sure that they should evolv e them in a unique way
to suit their project requirements. Students can be informed to refer Digital India portal, SIH portal or any
other hackathon portal for problem selection.
• Topics can be finalized with respect to following criterion:
Topic Selection : The topics selected should be novel in nature (Product based, Application based, or
Research based) or should work towards removing the lacuna in currently existing
systems.
Technology Used: Use of the latest technology or modern tools can be encouraged .

• Students should not repeat work done previously (work done in the last three years).
• Project work must be carried out by a group of at least 2 students and a maximum of 4.
• The project work can be undertaken in a research institute or organization/Industry/any business
establishment. (Out -house projects)
• The project proposal presentations can be scheduled according to the domains and should be judged by
faculty who are experts in the domain.
• The head of department and senior staff along with project coordinators will take decision regarding final
selection of projects.
• Guide allocation should be done, and students have to submit weekly progress reports to the internal guide.
• Internal guide has to keep track of the progress of the project and also has to maintain attendance report.
This progress report can be used for awarding term work marks.
• In the case of industry/ out -house projects, a visit by internal guide will be preferred and external members
can be called during the presentation at various levels.

Project Report Format:

At the end of semester, each group needs to prepare a project report as per the guidelines issued by the
University of Mumbai.

A project report should preferably contain at least following details:
• Abstract
• Introduction
• Literature Survey/ Existing system
• Limitation Existing system or research gap
• Problem Statement and Objective
• Proposed System
• Analysis/Framework/ Algorithm
• Design details
• Methodology (your approach to solve the problem) Proposed System
• Experimental Set up
• Details of Database or details about input to systems or selected data
• Performance Evaluation Parameters (for Validation)
• Software and Hardware Set up
• Implementation Plan for Next Semester
• Timeline Chart for Term1 and Term -II (Project Management tools can be used.)
• References

Desirable

• Students can be asked to undergo some Certification course (for the technical skill set that will be useful
and applicable for projects.

Page 86

Term Work:

Distribution of marks for term work shall be done based on following:
1. Weekly Log Report
2. Project Work Contribution
3. Project Report (Spiral Bound) (both side print)
4. Term End Presentation (Internal)
The final certification and acceptance of TW ensures satisfactory performance on the above aspects.
Oral and Practical:

The Oral and Practical examination (Final Project Evaluation) of Project 1 should be conducted by
Internal and External examiners approved by University of Mumbai at the end of the semester.

Suggested quality evaluation parameters are as follows:

1. Quality of problem selected.
2. Clarity of problem definition and feasibility of problem solution
3. Relevance to the specialization / industrial trends
4. Originality
5. Clarity of objective and scope
6. Quality of analysis and design
7. Quality of written and oral presentation
8. Individual as well as teamwork

Page 87

Program Structure for Fourth Year Engineering Semester VII & VIII
UNIVERSITY OF MUMBAI
(With Effect from 2023 -24)
Semester VIII


Course
Code
Course Name Teaching Scheme
(Contact Hours)
Credits Assigned
Theory Pract.
Tut. Theory Pract. Total
IoTCSBCC
801 NFT & DeFi (Decentralized
Finance) 3 -- 3 -- 3
IoTCSBC D
O801X Department Optional Course
– 5 3 -- 3 -- 3
IoTCSBC D
O802X Department Optional Course
– 6 3 -- 3 -- 3
IoTCSBC I
O801X Institute Optional Course – 2
3 -- 3 -- 3
IoTCSBCL
801 Capstone Lab -- 2 -- 1 1
IoTCSBCL
802 IoT Automation Lab -- 2 -- 1 1
IoTCSBCP
801 Major Project II
-- 12# -- 6 6
Total 12 16 12 8 20



Course
Code



Course Name Examination Scheme
Theory Term
Work Prac
/oral Total

Internal Assessment End
Sem
Exam Exam.
Duratio n
(hrs,)
Test1 Test2 Avg
IoTCSBCC
801 NFT & DeFi (Decentralized
Finance) 20 20 20 80 3 -- -- 100
IoTCSBC D
O801X Department Optional Course
– 5 20 20 20 80 3 -- -- 100
IoTCSBC D
O802X Department Optional Course
– 6 20 20 20 80 3 -- -- 100
IoTCSBC I
O801X Institute Optional Course – 2
20 20 20 80 3 -- -- 100
IoTCSBCL
801 Capstone Lab -- -- -- -- -- 25 25 50
IoTCSBCL
802 IoT Automation Lab -- -- -- -- -- 25 25 50
IoTCSBCP
801 Major Project II
-- -- -- -- -- 100 50 150
Total -- -- 80 320 -- 150 100 650
# indicates work load of Learner (Not Faculty), for Major Project

Page 88

Students group and load of faculty per week.

Mini Project 1 and 2 :
Students can form groups with minimum 2 (Two) and not more than 4 (Four) Faculty
Load : 1 hour per week per four groups



Major Project 1 and 2 :
Students can form groups with minimum 2 (Two) and not more than 4 (Four) Faculty
Load : In Semester VII – ½ hour per week per project group
In Semester VIII – 1 hour per week per project group



IoTCSBC DO801X Department Optional Course – 5
IoTCSBCDO8 011 Emerging Applications of Blockchain in industry
IoTCSBCDO8 012 IoTs & Embedded Security
IoTCSBCDO8 013 Information Retrieval System
IoTCSBCDO8 014 Intelligent Forensic

IoTCSBC DO802X Department Optional Course –6
IoTCSBCDO8 021 IoT for Smart Grids
IoTCSBCDO8 022 Metaverse
IoTCSBCDO8 023 Green IT
IoTCSBCDO8 024 Cyber Security laws & legal accepts

# Institute Level Optional Course (ILO)

Every student is required to take one Institute Elective Course for Semester VI II, which is
not closely allied to their disciplines. Different sets of courses will run in the both the
semesters.

ILO801X Institute Optional Course – 2 ( Common for all branches will be notified )
ILO8011 Project Management
ILO8012 Finance Management
ILO8013 Entrepreneurship Development
and Management
ILO8014 Human Resource Management
ILO8015 Professional Ethics and CSR
ILO8016 Research Methodology
ILO8017 IPR and Patenting
ILO8018 Digital Business Management
ILO8019 Environmental Management

Page 89

Theory Practical Tutorial Theory Practical/Oral Tutorial Total
IoTCSBCC801 NFT & DeFi
(Decentralized
Finance) 03 -- -- 03 -- -- 03

Subject Code Subject Name Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End
Sem.
Exam Test1 Test
2 Avg. of 2
Tests
IoTCSBCC801 NFT & DeFi
(Decentralized
Finance) 20 20 20 80 -- -- -- 100

Sr.
No. Course Objectives
The course aims:
1. To gain a fundamental understanding of NFTs and delve into the various uses and practical applications
of NFTs.
2. To examine the process of tokenizing assets and investigate the various standards and protocols
associated with NFTs.
3. To furnish information on marketplaces dedicated to the buying, selling, and creation of NFTs.
4. To understand the basic principles and concepts of DeFi
5. To recognize the obstacles and potential advantages pertaining to security within the realm of DeFi
6. To gain knowledge about various applications and uses of DeFi.

Sr. No. Course Outcomes Cognitive levels of
attainment as per Bloom’s
Taxonomy
On successful completion, of course, learner/student will be able to:
1. To grasp the fundamental principles and ideas behind NFTs. L1
2. To investigate the process of tokenizing assets and explore the diverse
standards and protocols associated with NFTs. L1, L2
3. To utilize acquired knowledge about NFT marketplaces and platforms to
engage in activities such as purchasing, selling, and creating NFTs. L1, L2
4. To delve into the core principles and concepts of DeFi, examining its
fundamental aspects and foundational principles. L1, L2
5. To recognize the obstacles and potential advantages in terms of security
within the realm of DeFi, while understanding the challenges and
opportunities that arise in safeguarding DeFi protocols and user assets. L1
6. To implement and utilize DeFi principles and technologies in practical,
real-world applications. L1, L2

Prerequisite: Blockchain Technology
DETAILED SYLLABUS:

Page 90

Sr.
No. Module Detailed Content Hours CO
Mapping
0 Prerequisite Blockchain, cryptocurrency, smart contracts, Web3 02 1
I Introduction to NFTs Definition of NFTs, history and development of NFTs, characteristics
of NFTs, types of NFTs, difference between fungible and non -
fungible tokens, comparison of NFTs with other digital assets like
cryptocurrencies, working of NFTs, advantages and opportunities of
NFT investments, risks and challenges of NFT investments, buying
and selling of NFTs, legal aspects of NFTs, potential applications and
developments of NFTs.
Self-study: Mapping of NFTs wit h potential applications. 06 1
II Tokenization & NFT
standards Definition of tokenization, its advantages and disadvantages, process
of tokenization, token offerings (initial coin offerings (ICOs), security
token offerings (STOs), initial exchange offerings (IEOs), equity
token offerings (ETOs), and decentralized autonomous initial coin
offerings (DAICOs)), ERC -721, ERC -1155, ERC -994, ERC -420,
ERC -809

Self-study: ERC -1201, ERC -998, NEO token standards 07 2
III NFT marketplaces
and platforms Popular NFT marketplaces and platforms for buying, selling, and
creating NFTs such as OpenSea, Rarible, SuperRare, Nifty Gateway,
NBA Top Shot, creating and minting NFTs

Self-study: Other NFT marketplaces and platforms: Axie Infinity,
Wax (Atomic Hub), Foundation, VeVe, Known Origin, Myth Market,
Wrap -Up 04 3
IV Fundamentals of
DeFi Financial markets (trading and exchanges), applications of blockchain
in finance including insurance, post -trade settlement, financial crime
prevention, and payments. What is DeFi, difference between
TradFi/CeFi and DeFi, DeFi properties, DeFi layered arch itecture,
DeFi primitives, DeFi services (asset tokenization, decentralized
exchanges (DEX) —Automated Market Maker (AMM), order book -
based DEX, DEX aggregators, flash loans, derivatives, money
streaming, yield farming, insurance, and decentralized lending and
borrowing), DeFi benefits

Self-study: DEX examples: Uniswap, Bancor, WavesDEX, 0x, and
IDEX. Applications of NFTs in DeFi: Collateralized loans, Fractional
ownership, Gamification, etc. 09 4
V DeFi Security Issues on all DeFi layers: Network attacks (Eclipse, DoS attacks),
Consensus attacks (51% attacks, double -spending, selfish mining),
Smart contract code bugs (reentrancy, authorization), DeFi Protocol
Composability attacks (excessive arbitrage between pools, flash
loans, oracle attacks), bridge at tacks, Governance attacks

Self-study: Open Research Challenges in DeFi 06 5
VI DeFi Applications DeFi Apps, advantages of DeFi apps over traditional financial
systems, Popular DeFi Apps: Instadapp (INST), Compound (COMP),
PancakeSwap (CAKE), JustLend (JST), Convex Finance (CVX),
NFT for metaverse.

Self-study: Curve (CRV), Uniswap (UNI), Aave (AAVE), Lido
(LDO), Maker (MKR), MakerDAO 05 6

Page 91

Text Books:
1. What are NFTs? - 4 YOU - The NFT comprehensive guidebook by Holger Kiefer (2023)
2. NFT Art and Collectibles for Beginners by Chris Collins (2021)
3. The NFT Handbook by Matt Fortnow and QuHarrison Terry (2021)
4. Mastering Blockchain by Imran Bashir (4th Edition) (2023)
5. DeFi for Dummies by Seoyoung Kim (2022)
6. NFT for Dummies by Tiana Laurence and Seoyoung Kim (2021)
References:
1. NFT for Beginners by Clark Griffin (2022)
2. NFT: The Ultimate Guide to Invest in Non -Fungible Tokens and Create Your Digital Assets with Crypto Collectibles
Art
+ NFT Virtual Real Estate by Brendon Stock (2020)
3. NFT for Beginners: Crypto Art AI (2021)
4. Decentralized Finance: From Core Concepts to DeFi Protocols for Financial Transactions by Thomas K. Birrer,
Dennis Amstutz, Patrick Wenger (2023)
5. Stake Hodler Capitalism: Blockchain and DeFi (Decentralized Finance) by Amr Hazem Wahba M etwaly (2021)
6. How to DeFi by Darren Lau, Daryl Lau, Teh Sze Jin, Kristian Kho, Erina Azmi, TM Lee, Bobby Ong (2020)
7. Business of Decentralized Finance by Sam Ghosh (2022)

Online References:
1. NPTEL: Blockchain and its Applications (Link: https://onlinecourses.nptel.ac.in/noc22_cs44/preview)
2. Udemy: The Complete NFT Course - Learn Everything About NFTs (Link: https://www.udemy.com/course/the -
complete -nft-course -learn -everything -about -nfts/)
3. Udemy: Decentralized Finance (DeFi) Fundamentals (L ink: https://www.udemy.com/course/decentralized -finance -
defi-fundamentals/)
4. A Survey of DeFi Security: Challenges and Opportunities by Wenkai Li, Jiuyang Bu, Xiaoqi Li, Hongli Peng,
Yuanzheng Niu, Yuqing Zhang (2022) (Link: https://arxiv.org/abs/2206.11821 )
5. Decentralized Finance, MOOC, Fall 2022 (Link: https://defi -learning.org/f22)

Assessment:
Internal Assessment (IA) for 20 marks:
● IA will consist of Two Compulsory Internal Assessment Tests. Approximately 40% to 50% of syllabus content must
be covered in First IA Test and remaining 40% to 50% of syllabus content must be covered in Second IA Test
Question paper format
● Question Paper will comprise of a total of six questions each carrying 20 marks Q.1 will be compulsory and
should cover maximum contents of the syllabus.
● Remaining questions will be mixed in nature (part (a) and part (b) of each question must be from different
modules. For example, if Q.2 has part (a) from Module 3 then part (b) must be from any other Module randomly
selected from all the modu les)
● A total of four questions needs to be answered.

Page 92

Subject Code Subject Name Theory Practical Tutorial Theory Practical/Oral Tutorial Total
IoTCSBC DO8011 Emerging
Applications of
Blockchain in
industry 03 -- -- 03 -- -- 03

Subject Code Subject Name Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal Assessment End
Sem.
Exam Test1 Test
2 Avg. of
2 Tests
IoTCSBC DO801 1 Emerging
Applications of
Blockchain in
industry
20 20 20 80 -- -- -- 100

Course Objectives:

Sr. No. Course Objectives
The course aims:
1 To study the fundament al concepts of blockchain technology and its relevance to Supply Chain and
Logistics Industry .
2 To study t he concepts of blockchain concepts and collate with Finance and Banking .
3 To study t he concepts of blockchain concepts and collate with Healthcare Industry.
4 To study t he concepts of blockchain concepts and collate with Energy Trading and Grid
Management .
5 To study t he concepts of blockchain concepts and collate with Real Estate Sector .
6 To study the concepts of decentralized applications and its applicability in web application
development.

Course Outcomes:

Sr. No. Course Outcomes Cognitive levels of
attainment as per
Bloom’s Taxonomy
On successful completion, of course, learner/student will be able to:
1 Interpret blockchain -based concepts to Supply Chain and Logistics Industry . L3
2 Demonstrate blockchain -based concepts to Finance and Banking . L3
3 Demonstrate blockchain -based concepts to Healthcare Industry . L2
4 Use blockchain -based concepts to Energy Trading and Grid Management . L2
5 Interpret blockchain -based concepts to Real Estate Sector . L5
6 Demonstrate the understanding of decentralization and its use in application
development . L6

Prerequisite: Introduction to Distributed Systems and fundamental blockchain technology concepts
DETAILED SYLLABUS:
Sr. Module Detailed Content Hours CO

Page 93

No. Mapping
0 Prerequisite Introduction to Blockchain Technology: Definition and core
principles of blockchain, Distributed ledger technology and its
features, Types of blockchain networks (public, private,
consortium). Cryptographic primitives (hash functions, digital
signatures), Public -key cryptography and key management in
blockchain, Security challenges and countermeasures in
blockchain networks. 02 --
I Blockchain for
Supply Chain and
Logistics Industry Role of key supply chain objectives, Traceability and
Provenance: Track and record product's journey, ensuring
transparency, verifying authenticity, preventing counterfeiting.
Inventory Management: Real -time visibility into inventory
levels, efficiency improvement and error minimization.
Supplier Verification: Secure verificat ion of suppliers'
credentials and certifications, enhancing trust and reducing
supply chain risks. Applications of blockchain for weapon
tracking. 06 CO1
II Applications of
Blockchain in
Finance and Banking Challenges in Finance Sector, Know Your Customer (KYC):
Blockchain -based KYC solutions to securely verify and share
customer information across multiple financial institutions,
Cross -border Payments, Trade Finance. Stock Trading,
Insurance, Mortgages, Smart Contracts: Automating
contractual agreements, streamline processes and reduce fraud.
improving compliance and reducing duplication.
06 CO2
III Applications of
Blockchain in
Healthcare Industry Challenges in Healthcare, Medical Records: Securely store and
share patient records, ensuring data integrity, interoperability,
and patient privacy. Drugs supply chain management, Patient
and Provider Identity management.
Clinical Trials: Streamlining the management of clinical trial
data, ensuring transparency and immutability of trial results.
Drug Tr aceability: Track the entire supply chain of
pharmaceuticals, reducing the risk of counterfeit drugs and
ensuring patient safety. IoT based medical delivery drones.
Blockchain for pharmaceutical industries and
biomanufacturing, “FabRec” platform.
06 CO3
IV Applications of
Blockchain in Energy
Trading and Grid
Management Peer-to-Peer Energy Trading: Blockchain enabled
decentralized energy trading among prosumers, promoting
renewable energy adoption and reducing reliance on traditional
energy sources. Grid Management: Blockchain -based systems
to enhance the efficiency of energy grid management,
including demand response, grid balancing, and asset
management. 06 CO4

Page 94

V Applications of
Blockchain in Real
Estate sector Property Title Management: Decentralized and transparent
system for recording and transferring property titles, reducing
fraud and disputes. Smart Contracts for Rentals: Blockchain -
based smart contracts to automate rental agreements, enabling
self-execution of payments and conditions. Blockchain -
enabled cyber -physical systems. Characteristics and
Challenges in blockchain -enabled CPS systems. 06 CO5
VI Decentralized Web Difference between Web2 and Web3, introduction to Web3,
web3 stack and architecture, How Web3 works, web3 wallets
and tokens, security aspects in web3, Web3 use cases. 06 CO6

Text Books:
1. Blockchain Technology Kindle Edition by Chandramouli Subramanian , Asha A George , Abhilash K
A, Meena Karthikeyan . Bikramaditya Singhal, Gautam Dhameja, Priyansu Sekhar Panda,
2. Beginning Blockchain A Beginner's Guide to Building Blockchain Solutions, Apress, 2018.
3. Web3 - The Decentralized Web - The Complete Guide: Why the Decentralized Web3 is The Future
[dApps, Smart Contracts, De centralization, NFTs, Blockchain] Paperback – October 13, 2021 by Alex
Anderson.
4. Kirankalyan Kulkarni, Learn Bitcoin and Blockchain, Packt, 2018
5. Sandeep Kumar Panda, Vaibhav Mishra, Sujata Priyambada Dash, Ashis Kumar Pani, Recent Advances in
Blockchain Technology Real -World Applications, Springer, 2023

References:
1. Blockchain Technology for Emerging Applications by SK Hafizul Islam, Arup Kumar Pal, Debabrata Samanta,
Siddhartha Bhattacharyya.
2. Blockchain: A Practical Guide to Developing Business, Law, and Technology Solutions" by Joseph J. Bambara and
Paul R. Allen
3. Blockchain Basics: A Non -Technical Introduction in 25 Steps by Daniel Drescher
4. A Brief Introduction to Web3: Decentralized Web Fundamentals for App Development
by Shashank Mohan Jain
5. "Mastering Blockchain: Distributed Ledger Technology, Decentralization, and Smart Contracts Explained" by Imran
Bashir 4th Edition.
6. "Blockchain for Enterprise" by Narayan Prusty Packt Publishing
7. "Blockchain for Business 2019" by Peter Lipovyanov and Ian Khan
8. "Blockch ain: A Practical Guide to Developing Business, Law, and Technology Solutions" by Joseph J. Bambara and
Paul R. Allen
9. "The Business Blockchain: Promise, Practice, and Application of the Next Internet Technology" by William Mougayar


Online References:
1. Live Demo : https://andersbrownworth.com/blockchain/
2. Hyperledger Fabric - https://www.hyperledger.org/projects/fabric


Assessment:
Internal Assessment (IA) for 20 marks:
● IA will consist of Two Compulsory Internal Assessment Tests. Approximately 40% to 50% of syllabus content must
be covered in First IA Test and remaining 40% to 50% of syllabus content must be covered in Second IA Tes t
Question paper format

Page 95

● Question Paper will comprise of a total of six questions each carrying 20 marks Q.1 will be compulsory and
should cover maximum contents of the syllabus.
● Remaining questions will be mixed in nature (part (a) and part (b) of each question must be from different
modules. For example, if Q.2 has part (a) from Module 3 then part (b) must be from any other Module randomly
selected from all the modules)
● A total of four questions needs to be answered.









Course
Code Course Name Theory Practical Tutorial Theory Oral Tutorial Total
IoTC SBCD
O8012 IoTs &
Embedded
Security 03 -- -- 03 -- -- 03

Course
Code Course Name Examination Scheme
Theory Marks
Term
Work Practic
al Oral Total Internal assessment
End Sem.
Exam Test1 Test 2 Avg.
of 2
Tests
IoTCSBCD
O8012 IoTs &
Embedded
Security 20 20 20 80 -- -- -- 100

Course Objectives:
Sr. No. Course Objectives
The course aims:
1 To understand the fundamentals of IoTs and embedded systems, including their architecture, components,
and communication protocols.
2 To gain knowledge of common security vulnerabilities and threats specific to IoT devices and embedded
systems.
3 To develop skills to analyze, assess, and mitigate security risks associated with IoTs and embedded
systems.
4 To learn various techniques and tools for securing IoT devices, networks, and communication channels.
5 To explore best practices for designing and implementing secure IoT architectures and protocols.
6 To stay updated with emerging trends, advancements, and challenges in IoT security and embedded
systems.

Course Outcomes:

Sr. No. Course Outcomes Cognitive levels of
attainment as per
Bloom’s Taxonomy
On successful completion, of course, learner/student will be able to:

Page 96

1 Demonstrate a comprehensive understanding of the concepts, principles, and
challenges associated with securing IoTs and embedded systems. L1, L2, L3
2 Analyze and assess the security vulnerabilities and risks in IoT devices,
networks, and protocols, and propose effective countermeasures. L1, L2, L3, L4
3 Apply various techniques and tools for conducting vulnerability assessments
and penetration testing on IoT devices and systems. L1, L2, L3
4 Design and implement secure architectures and protocols for IoT
deployments, considering data security, privacy, and authentication
requirements. L1, L2, L3, L4, L5, L6
5 Evaluate and select appropriate security measures, technologies, and
frameworks for mitigating security risks in IoT and embedded systems. L1, L2. L3, L4, L5
6 Stay updated with the latest advancements and emerging trends in IoT
security and apply critical thinking to adapt security strategies to evolving
threats. L1, L2

Prerequisite: Computer Networks, Basic Programming, Operating Systems, Cyber Security Fundamentals.



DETAILED SYLLABUS:

Sr.
No. Module Detailed Content Hours CO
Mapping
0 Prerequisite Computer Networks, Basic Programming, Operating Systems,
Cyber Security Fundamentals. 02 --
I Introduction to
IoTs and
Embedded
Systems
Security Definition and characteristics of IoTs Overview of embedded
systems and their role in IoTs, Importance of security in IoTs
and embedded systems, Common IoT applications and their
security implications, Challenges and risks in IoTs and
embedded systems security, Introduction to security frameworks
and standards for IoTs
Self-learning Topics: Research current and emerging IoT
technologies and applications, investigate real -world exam ples
of IoT security breaches and their impact, Explore IoT security
frameworks and standards. 05 CO1
II IoT Device
Architecture
and Security IoT device components: sensors, actuators, microcontrollers
Secure device provisioning and authentication mechanisms
Firmware security: secure boot, firmware updates, and integrity
checks, Hardware security measures: tamper resistance, secure
elements, trusted platform modules (TPM), Security
considerations for IoT gateways and edge devices
Self-learning Topics: Learn about different types of IoT devices
and their architectures, Research secure device provisioning and
bootstrapping techniques, Explore hardware -based security
measures, such as secure elements and trusted platform modules
(TPMs) 07 CO2
III Communicatio
n Protocols
and Network
Security for
IoTs Overview of communication protocols used in IoTs (e.g.,
MQTT, CoAP, HTTP) IoT network architectures: star, mesh,
tree, and hybrid topologies, Security mechanisms for IoT
communication: encryption, authe ntication, access control.
Network -level security protocols for IoTs: IPsec, DTLS, TLS
Security considerations for wireless IoT networks (e.g., Zigbee,
Z-Wave, Wi -Fi)
Self-learning Topics: Dive deeper into specific IoT
communication protocols, investigate security vulnerabilities
and attacks related to IoT communication protocols, Research
IoT network security technologies 07 CO3

Page 97

IV Vulnerability
Assessment
and
Penetration
Testing for
IoTs Understanding common vulnerabilities in IoT devices and
systems, IoT threat modeling: identifying and assessing risks.
Techniques for vulnerability assessment in IoT environments
Penetration testing methodologies for IoT devices and networks
Remediation strategies and best practices for IoT security
Self-learning Topics: Learn about common vulnerabilities and
exploits specific to IoT devices and systems, explore tools and
methodologies for conducting vulnerability assessments on IoT
devices 05 CO4
V Data Security
and Privacy in
IoTs Data security challenges in IoTs: confidentiality, integrity, and
availability, Secure data transmission and encryption techniques
in IoTs, Privacy considerations in IoT data collection and storage
Privacy -enhancing technologies for IoTs: anonymization,
pseudonymization
Compliance with data protection regulations (e.g., GDPR,
CCPA) in IoT deployments

Self-learning Topics: Study encryption algorithms commonly
used in IoT data protection, Investigate privacy -enhancing
technologies like differential privacy and homomorphic
encryption.
Research legal and regulatory frameworks related to IoT data
security and privacy. 07 CO5
VI Emerging
Trends and
Advanced
Topics in IoT
Security Blockchain technology for secure and decentralized IoT systems
Machine learning and AI -driven security solutions for IoTs
Edge computing and fog computing in enhancing IoT security
and performance. Security considerations for IoT in critical
infrastructures (e.g., healthcare, smart cities) Ethical and social
implications of IoT security and privacy
Self-learning Topics: Explore cutting -edge research papers
and publications on IoT security, Investigate the role of
blockchain technology in securing IoT systems, Learn about
machine learning and AI -driven security solutions for IoT threat
detection and mitigation 06 CO6

Textbooks:
1. "Internet of Things (A Hands -on-Approach)" by Arshdeep Bahga and Vijay Madisetti
2. "Practical Internet of Things Security" by Brian Russell, Drew Van Duren, and John R. Vacca
3. "Building the Internet of Things: Implement New Business Models, Disrupt Competitors,
Transform Your Industry" by Maciej Kranz
References Books:
1. "Internet of Things: Principles and Paradigms" edited by Rajkumar Buyya, Amir Vahid Dastjerdi,
and Sriram Venugopal
2. "Security and Privacy in Internet of Things (IoTs): Models, Algorithms, and Implementations"
edited by Fei Hu
Online References:
1. IoT Top 10: https://owasp.org/www -project -iot-top-10/
2. IoT Security Foundation: https://www.iotsecurityfoundation.org/
3. NIST Cybersecurity for IoT Program: https://www.nist.gov/programs -projects/cy bersecurity -iot-
program
4. IoT Security Resources: https://www.sans.org/iot -security/

Assessment:
Internal Assessment (IA) for 20 marks:

Page 98

● IA will consist of Two Compulsory Internal Assessment Tests. Approximately 40% to 50% of syllabus
content must be covered in First IA Test and remaining 40% to 50% of syllabus content must be covered in
Second IA Test
Question paper format

● Question Pa per will comprise of a total of six questions each carrying 20 marks. Q.1 will be compulsory
and should cover maximum contents of the syllabus.
● Remaining questions will be mixed in nature (part (a) and part (b) of each question must be from different
modules. For example, if Q.2 has part (a) from Module 3 then part (b) must be from any other Module randomly
selected from all the modules)
● A total of four questions needs to be answered.






Course Code Course Name Theory Practical Tutoria
l Theory Oral Tutorial Total
IoTCSBCD
O8013 Information
retrieval system 03 -- -- 03 -- -- 03

Course
Code Course Name Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End
Sem.
Exam Test1 Test 2 Avg. of 2
Tests
IoTCSBCD
O8013 Information
retrieval
system 20 20 20 80 -- -- -- 100

Course Objectives: Six Course Objectives
1. To learn the fundamentals of the information retrieval system.
2. To classify various Information retrieval models.
3. To demonstrate the query processing techniques and operations
4.To compare the relevance of query languages for text and multimedia data
5. To analyse the significance of various multimedia information re trieval models.
6. To understand IoT data management and analytics.
Course Outcomes: Six Course outcomes

Page 99

Sr. No. Course Outcomes Cognitive levels of
attainment as per
Bloom’s
Taxonomy
On successful completion, of course, learner/student will be able to:
1 Define the objectives of the basic concepts of the Information retrieval system. L1,
2 Apply different information retrieval models to real time world problems. L2, L3
3 Solve text and multimedia retrieval queries and their operations. L3, L4
4 Apply text processing techniques and operations in the Information Retrieval
system. L3, L4
5 Analyze various multimedia Information Retrieval models. L3
6 Apply different IoT data management techniques L3

Prerequisite: Indexing and searching Algorithms,Internet of Things (IoT) Fundamentals

DETAILED SYLLABUS: t
Sr.
No. Module Detailed Content Hours CO
Mapping
0 Prerequisite Indexing and searching Algorithms, Internet of Things
(IoT) Fundamentals 02
I Introduction to
Information
Retrieval System Motivation, Basic Concepts, The Retrieval Process,
Information System: Components, parts and types on
information system; Definition and objectives on
information retrieval system, Information versus Data
Retrie val. Search Engines and browsers
Self-learning Topics : Search Engines , Search API 06 CO1
II IR Models Modeling: Taxonomy of Information Retrieval
Models,Retrieval: Formal Characteristics of IR
models, Classic Information Retrieval, Alternative
Set Theoretic models, Probabilistic Models,
Structured text retrieval Models, models for
Browsing;
Self-learning Topics: Terrier - IR Platform and
similar IR Platforms 06 CO2
III Query Processing
and Operations Query Languages: Keyword based Querying, Pattern
Matching, Structural Queries, Query Protocols;
Query Operations: User relevance feedback
Self-learning Topics: Proximity Queries and
Wildcard Queries 05 CO3
IV Text Processing Text and Multimedia languages and properties:
Metadata, Markup Languages, Multimedia; Text
Operations: Document Preprocessing, Document
Clustering.
Self-learning Topics: Digital Library : Greenstone
06 CO4
V Multimedia IR
models Inverted files, Other indices for text, Boolean
Queries, Sequential Searching, Pattern Matching,
Structural Queries, Compression
Multimedia IR models: Data Modeling 08 CO5

Page 100

Multimedia IR: Indexing and Searching: - A Generic
Multimedia indexing approach, ,Automatic Feature
extraction; Searching Web: Challenges,
Characterizing the web, Search Engines. Browsing,
Meta searches, Searching using Hyperlinks
Self-learning Topics: Google Image Search Engine
VI IoT Data
Management and
Anlytics IoT Evolution, IoT Architectures, Resource
Management, IoT Data Management and Analytics,
IoT Applications

Self-learning Topics: ThingSpeak, Ubidots, AWS
cloud platform 06 CO6
Text Books:
1. Modern Information Retrieval, Ricardo Baeza -Yates,berthier Ribeiro - Neto, ACM Press - Addison Wesley
2. Information Retrieval Systems: Theory and Implementation, Gerald Kowaski, Kluwer Academic Publisher
3. Internet of Things - Principles and Paradigms, Rajkumar Buyya and Amir V. Dastjerdi, Elesvier
References:
1. Information Retrieval Implementing and Evaluating search Engines by Stefan Buttcher, Charles L.A. Clarke -The
MIT Press Cambridge, Massachusetts London, England
2. Introduction to Information Retrieval By Christopher D. Manning and Prabhakar Raghavan, Cambridge University
Press.
3. Introduction to Modern Information Retrieval. G.G. Chowdhury. NealSchuman.
Online References:
https://nptel.ac.in/courses/106101007
Assessment:
Internal Assessment (IA) for 20 marks:
● IA will consist of Two Compulsory Internal Assessment Tests. Approximately 40% to 50% of syllabus
content must be covered in First IA Test and remaining 40 % to 50% of syllabus content must be covered in Second
IA Test.
➢ Question paper format:
● Question Paper will comprise of a total of six questions each carrying 20 marks Q.1 will be compulsory
and should cover maximum contents of the syllabus.
● Remaining quest ions will be mixed in nature (part (a) and part (b) of each question must be from
different modules. For example, if Q.2 has part (a) from Module 3 then part (b) must be from any other Module
randomly selected from all the modules).
● A total of four questions need to be answered.

Page 101

Course Code Course Name Theory Practical Tutorial Theory Oral Tutoria
l Total
IoTCSBCD
O8014 Intelligent
Forensic 03 -- -- 03 -- -- 03

Course
Code Course Name Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End Sem.
Exam Test1 Test
2 Avg. of 2
Tests
IoTCSBC
DO8014 Intelligent
Forensic 20 20 20 80 -- -- -- 100

Course Objectives:
Sr. No. Course Objectives
The course aims:
1 Discuss the need of AI in Digital Forensics.
2 To understand the history of Digital Forensics.
3 To start a crime investigation based on different parameters.
4 To start a crime investigation based on different parameters.
5 To control, preserve, record, and recover evidence from the scene of an incident.
6 To identify Major AI tools and technology that are currently impacting the field of digital forensics.

Course Outcomes:
Sr.
No. Course Outcomes Cognitive levels of
attainment as per Bloom’s
Taxonomy
On successful completion, of course, learner/student will be able to:
1 Identify application of ML for Digital forensics. L1, L2
2 Understand and Analyze Forensics as Intelligence Sources. L1, L2, L4
3 Build Intelligence Features of Forensic Evidence. L1, L3
4 Build Evidence recovery, processing and Verify the Best Practice
Using the Main Forensic Evidence Types L1.L2, L3
5 Interpret and Investigate the Recovery of Forensic Evidence from the
crime scene. L1, L2, L4
6 Explore the Impact of implementing AI tools, tec hnology and
frameworks in digital forensics. L1, L2, L4


Prerequisite: Artificial Intelligence and Digital forensic.

Page 102

DETAILED SYLLABUS:
Sr.
No. Module Detailed Content Hours CO
Mapping
0 Prerequisite Basic of AI and DF 00 -
I Machine
Learning
Trends for
Digital
Forensics 1.1 Introduction
Need of Artificial Intelligence in Digital Forensics, Machine
Learning Basics, Machine learning for Digital Forensics.
Challenges of AI enabled DF.
1.2 Machine Learning Processes
Data Collection and Preprocessing, Training and Testing Phases
1.3 Applications of Machine Learning Models. Machine Learning
Types: Supervised Machine Learning, Unsupervised Machine
Learning, Semi -Supervised Machine Learning, Reinforceme nt
Learning
Self-Learning Topic: Case Study: Using ML for forensics. Using
the TON_IoT, Dataset for Forensics.



04



CO1
II Introducing
Forensic
Intelligence 2.1 The Beginnings of a Concept of Forensic Intelligence
Forensic Intelligence: Definition, The Concept of ‘Entities’ in
Police Recording Systems, Access to Forensic Support Resources,
Forensic Intelligence in Intelligence -Led Policing, The Origins of
Forensic Intelligence, Estimating the Number of Current Offenders
2.2 Police Intelligence Models
Police Intelligence Models and the Language of Intelligence -Led
Policing, The Four Levels of Crime Divisions in Crime,
COMSTAT, Intelligence Models, Intelligence Assets, Knowledge
Assets, System Assets, Forensics as Intelligence Sources
The Collection of Forensic Intelligence
Police Forensic Business Models
Self-Learning Topic: A Short History of Forensic Intelligence in
the Metropolitan Police,
An Early Forensic Intelligence Tool Mark Case Example from the
Late 1990s, Forensic Intelligence Development in the Metropolitan
Police, 2002 –2008.










8










CO2




III The Value of
Forensics in
Crime Analysis
and
Intelligence 3.1 Intelligence Features of Forensic Evidence Types
Linking Cases and Comparative Case Analysis
The Different Forms of Case Linking in Criminal, The Values of
Forensics in Case Linking Analysis, Receiver Operator
Characteristics, Truth and Probability,
The Crime Detection and Prosecution Rectangle,
Dealing with Forensic Crime Links and Clusters, Footwear
Evidence Frequency Eval uation
3.2 Forensic Legacy Data
Legacy Data and the FSS Sexual Assault, Forensic Intelligence
Service, Improving the Potential of Legacy Data Use, The
Importance of Regular Meetings, The Different Experiences of CSIs
and Analysts
Self-Learning Topic: A Foo twear Evidence Persistence Case
Example, A Linked Homicide Case Example, A Footwear Mark
Cluster Example, A Footwear Mark Cluster Example





7





CO3
IV Forensic
Evidence
Recovery,
Processing, and
Best Practice 4.1 Purposes and Objectives of Crime Scene Examinations
Inhibitors to Effective Uses of Crime Scene Examinations, Forensic
Recoveries in Linking Crimes, and in Contributing to the Production
of Intelligence Products, Rights or Not to Obtain or Seize Forensic
Material from Offenders

Page 103

4.2 The Ad vantages of Databasing and Managing Collections of
Forensic Evidence
A Scenes of Crime Field Force Checklist for Effective Management
of Forensics, Using Intervention Rates and Forensic Recovery
Frequencies in Crime Analysis, Issues around Positive and Neg ative
Management Techniques of Forensic Support, The Issue of Areas
Disclosed in Forensic Marks as an Enabler of Forensic Intelligence
4.3 Best Practice in Using the Main Forensic Evidence Types
Automatic Fingerprint Identification Systems and Their
Charac teristics, The Four Factors at Work in Existing Miss Rates
with AFIS, Forensic Strategies to Make the Best Use of AFIS,
Fingerprint Laboratory Support
4.4 Using DNA Matches and Crime Scene Links Effectively
An Inhibited DNA Casework Example, DNA Databases and eDNA,
Significance of DNA Forensic Crime Scene Intervention and
Recovery Rates, Forensic Problem Profiles and the Concept of the
Forensic Intelligence Report
Self-Learning Topic: An Example of Volume Crime Practices
Inhibiting a Serious Investigation





10





CO4
V Best Practice in
Recovery of
Forensic
Evidence from
Crime Scenes 5.1 Dealing with Crime Scenes
Crime Scene Examinations of Serious and Volume Crimes,
Recovery of Different Types of Evidence such as Footwear Marks,
Gelatine Lifters, Dealing with Dental Stone Casts, Marks in Snow,
Instrument (Tool) Marks
Isomark, Microsil, and Casting Putty Materials
5.2 Other Evidence Types
Ballistics, Manufacturing Marks, Evidential Value of
Manufacturing Marks, Physical Fits, Contact Trace Evidence,
Glass, Dealing with Suspects, Hair Combings, Paint Evidence
5.3 Miscellaneous Traces
Cosmetics, Oils and Greases, Plastics, Rubbers, and Adhesives,
Soil, Safe Ballast, and Building Materials, Metals, Other Noxious
Chemicals and Other Substances
Self-Learning Topic: Case study on recovery of digital evidence
such as CD, pen drive, Laptop 6

CO5
VI The impact of
automation and
artificial
intelligence on
digital
forensics AI and Automation, Automation in context of DF, use of AI in DF,
Framework of intelligent automation in digital forensics, Tools and
method of intelligent automation in digital forensic, Potential
impact of intelligent automation on digital forensic,
Tools: Magnet Axiom, Google Takeout Convertor, X -Ways
Forensics.
Self-Learning To pic: Study AI tools for report writing. 4

CO6

Textbooks and References:
1. Digital Forensics in the Era of Artificial Intelligence, Author: Nour Moustafa, Publisher: CRC Press,
2022.
2. Forensic Intelligence By Robert Milne ,1st Edition.
3. Forensic Biology, Author Richard Li, Publisher: CRC Press,2nd Edition.
4. Genetic Surveillance and Crime Control, Authors: Helena Machado and Rafaela Granja.
5. Predictive Policing and Artificial Intelligence, Author: John McDaniel, Ken Pease,1st Edition,2021

Online References:
1. Digital Forensics in the Era of Artificial Intelligence (ebooks.com)
2. Forensic Intelligence by Robert Milne (ebook) (ebooks.com)
3. The impact of automation and artificial intelligence on digital forensics (wiley.com)
4. Intelligence -Led Policin g: The New Intelligence Architecture (ojp.gov) .

Page 104

5. How AI can be used in forensic science: Challenges and prospects — DocInsights

Assessment :
Internal Assessment (IA) for 20 marks:
● IA will consist of Two Compulsory Internal Assessment Tests. Approximately 40% to 50% of syllabus
content must be covered in First IA Test and remaining 40% to 50% of syllabus content must be covered
in Second IA Test
Question paper format

● Question Paper will comprise of a total of six questions each carrying 20 marks. Q.1 will be
compulsory and should cover maximum contents of the syllabus.
● Remaining questions will be mixed in nature (part (a) and part (b) of each question must be from
different modules. For example, if Q.2 has part (a) from Module 3 then part (b) must be from any other
Module randomly selected from all the modules)
● A total of four questions needs to be answered.

Page 105

Subject Code Subject Name Theory Practical Tutorial Theory Practical/
Oral Tutorial Total
IoTCSBCDO80
21 IoT for Smart
Grids 03 -- -- 03 -- -- 03

Subject Code Subject Name Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End
Sem.
Exam Test1 Test 2 Avg. of 2
Tests
IoTCSBCDO
8021 IoT for
Smart Grids 20 20 20 80 -- -- -- 100

Course Objectives:

Sr. No. Course Objectives
The course aims:
1 To impart knowledge of futuristic power grid technology and the path on which development is taking
place.
2 To elaborate the fundamentals of various technologies and tools which will play a vital role in formation
of the Smart grids in near future.
3 To familiarize the students with distribution management systems in smart grid.
4 To expose students to various communication protocols used in smart grid.
5 To acquaint students with knowledge of smart meters and infrastructure in smart grid.
6 To understand different data management tools in a smart grid.

Course Outcomes:

Sr. No. Course Outcomes Cognitive levels of
attainment as per
Bloom’s Taxonomy
On successful completion, of course, learner/student will be able to:
1 To identify the role and significance of smart in future power systems L1, L2
2 To evaluate and compare applications of smart measurement and monitoring
technologies. L1, L2, L3, L4
3 To describe the role of a distribution management system in a smart grid. L1, L2
4 To select and analyze different communication protocols for differ ent applications
in a smart grid. L1, L2, L3, L4
5 To illustrate the importance of advanced metering infrastructure in smart grids. L1, L2, L3
6 To apply data management techniques and develop machine learning algorithms
for smooth operation of smart grid. L1, L2, L3, L4, L5

Prerequisite: IoTC601: IoT Architecture and Protocols, CSDO701X IoT for Smart Cities
DETAILED SYLLABUS:
Sr.
No. Module Detailed Content Hours CO
Mapping

Page 106

0 Prerequisite Fundamentals of Power Distribution System, Transmission
and Distribution, Power system Operation and Control,
Communication Networks 2 -
I Smart Grid:
Architecture and
Design 1.1.Introduction, Smart Grid Drivers
1.2.Transformation of the Grid
1.3.Characteristics of a Smart Grid
1.4.Smart Grid Technology Framework
1.5.Benefits of Smart grid

Self-Learning Topics: Smart grid architecture around the
globe 5 CO1
II Smart Grid
Technology 2.1 Smart Energy Resources - Renewable energy
generation
2.2 Energy storage
2.3 Electric vehicles
2.4 Energy Resources Integration Challenges,
Solutions, and Benefit
2.5 Smart Substation - Protection, Monitoring, and
Control Devices (IEDs) – Sensors – SCADA
2.6 IEC 61850 -Based Substation Design
2.7 Energy Management Systems
2.8 Wide Area Monitoring, Protection and Control
(WAMPAC)
2.9 Role of WAMPAC and Transmission Systems in a
Smart Grid

Self-Learning Topics: Microgrids versus smart grids 9 CO2
III Smart Distribution
Systems 3.1 Distribution Management Systems
3.2 Volt/VAr Control
3.3 Fault Detection, Isolation, and Service Restoration
3.4 Outage Management
3.5 Consumer Demand Management

Self-Learning Topics: High -Efficiency Distribution
Transformers 5 CO3
IV Communication
Networks and
Cyber Security 4.1 Communications Requirements for the Smart Grid
4.2 Communication layer - Home automation network,
Building automation network, Neighbourhood area
network, Local area network, Field area network, Wide
area network
4.3 Wireless Network Solutions for Smart Grid -
Cellular, RF Mesh
4.4 Communication Standards and Protocols - IEC
61850, DNP3 and IEC 60870 -5
4.5 IEEE C37.118, IEC 61968 -9 and MultiSpeak,
ANSI
4.6 Communications Challenges in the Smart Grid
4.7 Cyber Security for Smart Grid.

Self-Learning Topics: Probable attacks on smart grid. 8 CO4
V Smart Meters and
Advanced
Metering
Infrastructure
(AMI) 5.1 Evolution of the Electric Meter, and Meter Reading
5.2 AMI Drivers and Benefits
5.3 AMI Protocols, Standards, and Initiatives
5.4 AMI Security
5.5 AMI Needs in the Smart Grid
5.6 Phasor Measurement Unit.

Self-Learning Topics: Smart appliances 6 CO5

Page 107

VI Data Management
and Forecasting 6.1 Smart Grid Data Management, Characterization of
Smart Grid Data
6.2 Secure Information and Data Management
Architecture
6.3 Secure Data Management, Applications of Smart
Grid Data
6.4 Importance of machine learning in energy
forecasting, Big data in smart grid.

Self-Learning Topics: Renewable Energy Forecasting,
Fault Detection and Predictive Maintenance, Data
Visualization and Decision Support 4 CO6

Text Books:
1. James Momoh, “Smart Grid:Fundamentals of Design and Analysis”, IEEE Press and Wiley Publications, 2015
2. K. Liyanage, Jianzhong Wu, A. Yokoyama, Nick Jenkins J.Ekanayake, “Smart Grid: Technology and Applications”,
Wiley Publications , 2015
3. Stuart Borlase, “Smart Grids: Infras tructure, Technology, and Solutions”, CRC Press, 2012
4. Clark W. Gellings, “The Smart Grid: Enabling Energy Efficiency and Demand Response”, CRC Press

References:
1. Mini S. Thomas, John D McDonald, “Power System SCADA and Smart Grids”, CRC Press, 2015
2. Kenneth C.Budka, Jayant G. Deshpande, Marina Thottan, “Communication Networks for Smart Grids”, Springer,
2014.
3. H. T. Mouftah, and M. Erol -Kantarci, “Smart Grid: Networking, Data Management, and Business Models”, CRC
Press, 2016
4. Yang Xiao, “Communication a nd Networking in Smart Grids”, CRC Press, 2012

Online References:
1. https://onlinecourses.nptel.ac.in/noc23_ee60/preview
2. https://onlinecourses.nptel.ac.in/noc21_ee68/preview
Assessment:

Internal Assessment (IA) for 20 marks:
● IA will consist of Two Compulsory Internal Assessment Tests. Approximately 40% to 50% of syllabus
content must be covered in First IA Test and remaining 40% to 50% of syllabus content must be covered in Second
IA Test
⮚ Question paper format
● Question Paper will comprise of a total of six questions each carrying 20 marks Q.1 will be compulsory
and should cover maximum contents of the syllabus
● Remaining questions will be mixed in nature (part (a) and part (b) of each question must be from
differ ent modules. For example, if Q.2 has part (a) from Module 3 then part (b) must be from any other Module
randomly selected from all the modules)
● A total of four questions need to be answered.

Page 108

Subject
Code Subject
Name Theory Practical Tutoria
l Theor
y Practica
l/Oral Tutorial Tota
l
CSDO8023 Green IT 03 -- -- 03 -- -- 03

Subject
Code Subject
Name Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End
Sem.
Exam Test
1 Test 2 Avg. of 2
Tests
CSDO8023 Green IT
20 20 20 80 -- -- -- 100

Course Objectives:
1. To understand what Green IT is and How it can help improve environmental Sustainability.
2. To understand the principles and practices of Green IT.
3. To understand how Green IT is adopted or deployed in enterprises.
4. To understand how data centers, cloud computing, storage systems, software and networks can be
made greener.
5. To measure the Maturity of a Sustainable ICT world.
6. To implement the concept of Green IT in Information Assura nce in Communication and Social Media
and all other commercial field.
Course Outcomes:
Course
Outco
me Course Outcome Statement Cognitive
Levels of
attainment as
per Bloom’s
taxonomy
CO 1 Describe awareness among stakeholders and promote green
agenda and green initiatives in their working environments
leading to green movement. L1
CO2 Identify IT Infrastructure Management and Green Data
Center Metrics for software development L1 L2
CO3 Recognize Objectives of Green Network Protocols for Data
communication. L1 L2
CO4 Apply Green IT Strategies and metrics for ICT development. L1 L2 L3
CO5 Illustrate various green IT services and its roles L1 L2

Page 109

CO6 Demonstrate and use new career opportunities available in IT
profession, audits and others with special skills such as
energy efficiency, ethical IT assets disposal, carbon footprint
estimation, reporting and development of green products,
applications and services. L1 L2 L3

Prerequisite: Environmental Studies
DETAILED SYLLABUS:
Sr.
No. Module Detailed Content Hours CO
Mapping
0 Prerequisite Environmental Studies 2
I Introductio
n Environmental Impacts of IT, Holistic Approach to
Greening IT, Green IT Standards and Eco -Labeling,
Enterprise Green IT Strategy, Green IT: Burden or
Opportunity?
Hardware: Life Cycle of a Device or Hardware,
Reuse, Recycle and Dispose.
Software: Introdu ction, Energy Saving Software
Techniques, Evaluating and Measuring Software
Impact to Platform Power.
Self-Learning: Evaluating and Measuring software
impact to platform power 6 CO1
II Software
developme
nt and data
centers Sustainable Software, Software Sustainability
Attributes, Software Sustainability Metrics,
Sustainable Software Methodology, Data Centers
and Associated Energy Challenges, Data Centre IT
Infrastructure, Data Centre Facility Infrastructure:
Implications for Energy Efficiency, IT Infrastructure
Management, Green Data Centre Metrics
Self-learning Topics: Sustainable Software: A Case
Study, Data Centre Management Strategies 6 CO1 CO2
III Data
storage and
communica
tion Storage Media Power Characteristics, Energy
Management Techniques for Hard Disks, System -
Level Energy Management, Objectives of Green
Network Protocols, Green Network Protocols and
Standards
Self-learning Topics: System -Level Energy
Management 6 CO1 CO3
IV Information
systems,
green IT
strategy and
metrics Approaching Green IT Strategies, Business Drivers
of Green IT Strategy, Business Dimensions for
Green IT Transformation, Multilevel Sustainable
Information, Sustainability Hierarchy Models,
Product Level Information, Individual Level
Information, Functional Level Information,
Organizational Level Information, Regional/City
Level Information, Measuring the Maturity of
Sustainable ICT.
Self-learning Topics: Business Dimensions for
Green IT transformation. 6 CO1 CO4

Page 110

V Green IT
services
and roles Factors Driving the Development of Sustainable IT,
Sustainable IT Services (SITS), SITS Strategic
Framework, Sustainable IT Roadmap,
Organizational and Enterprise Greening, Information
Systems in Greening Enterprises, Greening the
Enterprise: IT Usage and Hardware, Inter -
organizational Enterprise Activities and Green
Issues, Enablers and Making the Case for IT and the
Green Enterprise.
Self-learning Topics: Inter-organizational
Enterprise Activities and Gre en Issues, Enablers and
Making the Case for IT and the Green Enterprise. 6 CO1 CO4
CO5
VI Managing
and
regulating
green IT Strategizing Green Initiatives, Implementation of
Green IT, Information Assurance, Communication
and Social Media, The Regulatory Environment and
IT Manufacturers, Nonregulatory Government
Initiatives, Industry Associations and Standards
Bodies, Green Buil ding Standards, Green Data
Centers, Social Movements and Greenpeace. Case
study on: Industry Sustainability with Green IT,
Managing Green IT, The energy consumption in
Torrent systems with malicious content, The use of
thin client instead of desktop PC
Self-learning Topics: Information Assurance, Green
Data Centers 7 CO1 CO5
CO6
Text Books:
1. San Murugesan, G. R. Gangadharan, Harnessing Green IT, WILEY 1st Edition -2018
2. Mohammad Dastbaz Colin Pattinson Babak Akhgar , Green Information Technology A Sustainable
Approach , Elsevier 2015
3. . Reinhold, Carol Baroudi, and Jeffrey Hill Green IT for Dummies, Wiley 2009
References:
1. Mark O’Neil, Green IT for Sustainable Business Practice: An ISEB Foundation Guide, BCS
2. Jae H. Kim, Myung J. Lee Green IT: Technologies and Applications, Springer, ISBN: 978 -3-642-
22178 -1
3. Elizabeth Rogers, Thomas M. Kostigen The Green Book: The Everyday Guide to Saving the Planet
One Simple Step at a Time, Springer
Assessment:

Internal Assessment (IA) for 20 marks:
● IA will consist of Two Compulsory Internal Assessment Tests. Approximately 40% to 50% of
syllabus content must be covered in First IA Test and remaining 40% to 50% of syllabus content must be
covered in Second IA Test
⮚ Question paper for mat
● Question Paper will comprise of a total of six questions each carrying 20 marks Q.1 will be
compulsory and should cover maximum contents of the syllabus

Page 111

● Remaining questions will be mixed in nature (part (a) and part (b) of each question must be from
different modules. For example, if Q.2 has part (a) from Module 3 then part (b) must be from any other
Module randomly selected from all the modules)
● A total of four questions need to be answered.



Course Code Course Name Theory Practical Tutorial Theory Oral Tutorial Total
IoTCSBCDO
8022
Metaverse
03 -- -- 03 -- -- 03

Course Code Course
Name Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End Sem.
Exam Test1 Test
2 Avg. of 2
Tests
IoTCSBCD
O8022
Metaverse
20 20 20 80 -- -- -- 100

Course Objectives:

Sr. No. Course Objectives
The course aims:
1 To study the concepts of Metaverse.
2 To study Metaverse and Web 3.0, Virtual Reality (VR), Augmented Reality (AR), and Mixed
Reality (MR), NFT in Blockchain.
3 To study the Metaverse technologies and protocols.
4 To study and identify the required infrastructure for Metaverse.
5 To Study various case studies of Metaverse.
6 To Study of Metaverse Immersive technology and Interfaces

Course Outcomes:

Sr. No. Course Outcomes Cognitive levels of
attainment as per
Bloom’s Taxonomy
On successful completion, of course, learner/student will be able to:
1 Explore the concepts of Metaverse. L3,L4
2 Describe the fundamental concepts needed for the metaverse. L1,L2
3 Explain the Metaverse technologies and protocols. L2,L4

Page 112

4 Construct the required infrastructure for Metaverse. L3
5 Describe Metaverse Immersive technology and Interfaces L1,L2
6 Express the different case studies of Metaverse L2,L3,L4



Prerequisite: Concepts of Blockchain

DETAILED SYLLABUS:
Sr.
No. Module Detailed Content Hours CO
Mapping
0 Prerequisite Basic Concepts of Blockchain Technology. 01 -
I Introduction: What is the Metaverse? History of metaverse, Evaluation of
Technology: Web, AR VR, 3D spaces. Immersive learning,
Blockchain, Decentralized commerce, challenges and opportunities of
metaverse
Self-learning: AR VR tools, Blockchain technology 04 CO1
II Fundamental
Concepts of
Metaverse Building block technology of metaverse, How Gaming + Web 3.0 +
Blockchain are Changing the Internet: Future of Internet. How
Metaverse is different from the Internet, Potential of Metaverse,
characteristics of metaverse. The Different Shapes of the Metaverse:
Games, NFTs (assets), Blockchain Protocols, Cryptocurrencies, etc.
Self-learning: Case Study on NFT, Cryptocurrency and Blockchain
platforms 08 CO2
III Metaverse
Technologies
and Protocols Metaverse technologies, principles, affordances and application,
Blockchain Protocols and Platforms Involved in the Metaverse,
Metaverse -Related Tokens, Blockchain NFT need for metaverse:
working principle of blockchain, NFT base d virtual assets in
metaverse, case study. How NFTs are Unlocking the Metaverse,
Potential working of ERC721 NFT 08 CO3
IV Metaverse
Infrastructure Access the metaverse, necessary hardware and Infrastructure,
Interface. Understanding Decentraland, native token MANA, creating
Avatar. Using metamask to access Decentraland, owning land to have
direct access of metaverse 07 CO4
V Metaverse
Immersive
technology
and Interfaces 3d Reconstruction, AI technology to analyses 3D Scan Virtual Reality
(VR) and Augmented Reality (AR), Mixed Reality (MR) and Extended
Reality (XR), Metaverse vs VR what is difference, IoT to bridge gap
between physical world and internet, Metaverse Interfa ces: Personal
Computer, Mobile Phone, AR Glasses, VR Goggles, Neuralink 08 CO5
VI Case studies
of Metaverse: Various use cases of metaverse, Industries Disrupted by the Metaverse:
Fashion, Marketing, Brands, Finance, Gaming, Architecture, Virtual
Shows/Concerts, Art Galleries and Museums. Virtual Business and
market: Investing in the Metaverse and Profit. Asset Classes Inside the
Metaverse. Metaverse Land Ownership - Property Investment 04 CO6

Text & Reference Books:
1. Metaverse For Beginners A Guide To Help You Learn About Metaverse, Virtual Reality And
Investing In NFTs By Andrew Clemens, 2022.
2. Extended Reality and Metaverse Immersive Technology in Times of Crisis, Springer
Proceedings in Business and Economics, Intern ational XR Conference 2022.

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3. Mystakidis, Stylianos, “
Metaverse”,Journal=Encyclopedia,2022, https://www.mdpi.com/2673 -8392/2/1/31
4. All One Needs to Know about Metaverse: A Complete Survey on Technolo gical Singularity,
Virtual Ecosystem, and Research Agenda, Technical Report · October 2021

Online References:
1. https://www.udemy.com/course/complete -metaverse -course -everything -about -ar-vr-
and-nft/


Assessment:
Internal Assessment (IA) for 20 marks:
● IA will consist of Two Compulsory Internal Assessment Tests. Approximately 40% to 50% of
syllabus content must be covered in First IA Test and remaining 40% to 50% of syllabus
content must be covered in Second IA Test
Question paper format

● Question Paper will comprise of a total of six questions each carrying 20 marks. Q.1 will be
compulsory and should cover maximum contents of the syllabus.
● Remaining questions will be mixed in nature (part (a) and part (b) of each question must be
from di fferent modules. For example, if Q.2 has part (a) from Module 3 then part (b) must be
from any other Module randomly selected from all the modules)
● A total of four questions needs to be answered.

Page 114

Course Code Course Name Theory Practical Tutorial Theory Oral Tutorial Total
IoTCSBCDO
8023 Green IT 03 -- -- 03 -- -- 03

Course
Code Course
Name Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End Sem.
Exam Test
1 Test
2 Avg. of 2
Tests
IoTCSBCD
O8023 Green IT
20 20 20 80 -- -- -- 100
Course Objectives:
Sr. No. Course Objectives
The course aims:
1 To understand what Green IT is and how it can help improve environmental Sustainability.
2 To understand the principles and practices of Green IT.
3 To understand how Green IT is adopted or deployed in enterprises.
4 To understand how data centers, cloud computing, storage systems, software and networks can be
made greener.
5 To measure the Maturity of a Sustainable ICT world.
6 To implement the concept of Green IT in Information Assurance in Communication and social
media and all other commercial fields.
Course Outcomes:
Sr.
No. Course Outcomes Cognitive levels of
attainment as per
Bloom’s Taxonomy
On successful completion, of course, learner/student will be able to:
1 Describe awareness among stakeholders and promote green agenda and
green initiatives in their working environments leading to green
movement. L1
2 Identify IT Infrastructure Management and Green Data Center Metrics for
software development L1, L2
3 Recognize Objectives of Green Network Protocols for Data
communication. L1, L2
4 Use Green IT Strategies and metrics for ICT development. L1, L2, L3
5 Illust rate various green IT services and its roles L1, L2
6 Use new career opportunities available in the IT profession, audits and
others with special skills such as energy efficiency, ethical IT assets L1, L2, L3

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disposal, carbon footprint estimation, reporting and development of green
products, applications and services.

Prerequisite: Environmental Studies





DETAILED SYLLABUS:
Sr.
No. Module Detailed Content Hours CO
Mapping
0 Prerequisite Environmental Studies 2
I Introduction Environmental Impacts of IT, Holistic Approach to Greening IT,
Green IT Standards and Eco -Labeling, Enterprise Green IT
Strategy, Green IT: Burden or Opportunity?
Hardware: Life Cycle of a Device or Hardware, Reuse, Recycle and
Dispose.
Software: Introduction, Energy Saving Software Techniques,
Evaluating and Measuring Software Impact to Platform Power.
Self-Learning: Evaluating and Measuring software impact to
platform power 6 CO1
II Software
development
and data centers Sustainable Sof tware, Software Sustainability Attributes, Software
Sustainability Metrics, Sustainable Software Methodology, Data
Centers and Associated Energy Challenges, Data Centre IT
Infrastructure, Data Centre Facility Infrastructure: Implications for
Energy Efficie ncy, IT Infrastructure Management, Green Data
Centre Metrics
Self-learning Topics: Sustainable Software: A Case Study, Data
Centre Management Strategies 6 CO1, CO2
III Data storage
and
communication
Storage Media Power Characteristics, Energy Management
Techniques for Hard Disks, System -Level Energy Management,
Objectives of Green Network Protocols, Green Network Protocols
and Standards
Self-learning Topics: System -Level Energy Management 6 CO1, CO3
IV Information
systems, green
IT strategy and
metrics Approaching Green IT Strategies, Business Drivers of Green IT
Strategy, Business Dimensions for Green IT Transformation,
Multilevel Sustainable Information, Sustainability Hierarchy
Models, Product Level Information, Individual Level Informati on,
Functional Level Information, Organizational Level Information,
Regional/City Level Information, Measuring the Maturity of
Sustainable ICT.
Self-learning Topics: Business Dimensions for Green IT
transformation. 6 CO1, CO4
V Green IT
services and
roles Factors Driving the Development of Sustainable IT, Sustainable IT
Services (SITS), SITS Strategic Framework, Sustainable IT
Roadmap, Organizational and Enterprise Greening, Information
Systems in Greening Enterprises, Greening the Enterprise: IT Usa ge
and Hardware, Inter -organizational Enterprise Activities and Green
Issues, Enablers and Making the Case for IT and the Green
Enterprise. 6 CO1, CO4
CO5

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Self-learning Topics: Inter-organizational Enterprise Activities and
Green Issues, Enablers and Making the Case for IT and the Green
Enterprise.
VI Managing and
regulating
green IT Strategizing Green Initiatives, Implementation of Green IT,
Information Assurance, Communication and social media, The
Regulatory Environment and IT Manufacturers, Nonregulatory
Government Initiatives, Industry Associations and Standards
Bodies, Green Buil ding Standards, Green Data Centers, Social
Movements and Greenpeace. Case study on: Industry
Sustainability with Green IT, Managing Green IT, The energy
consumption in Torrent systems with malicious content, The use of
thin client instead of desktop PC
Self-learning Topics: Information Assurance, Green Data Centers 7 CO1, CO5
CO6

Textbooks:
1. San Murugesan, G. R. Gangadharan, Harnessing Green IT, WILEY 1st Edition -2018
2. Mohammad Dastbaz Colin Pattinson Babak Akhgar , Green Information Technology A
Sustainable Approach , Elsevier 2015
3. Reinhold, Carol Baroudi, and Jeffrey Hill Green IT for Dummies, Wiley 2009

References:
1. Mark O’Neil, Green IT for Sustainable Business Practice: An ISEB Foundation Guide, BCS
2. Jae H. Kim, Myung J. Lee Green IT: Technologies and Applications, Springer, ISBN: 978-
3-642- 22178 -1
3. Elizabeth Rogers, Thomas M. Kostigen the Green Book: The Everyday Guide to Saving the
Planet One Simple Step at a Time, Springer

Assessment:
Internal As sessment (IA) for 20 marks:
● IA will consist of Two Compulsory Internal Assessment Tests. Approximately 40% to 50% of
syllabus content must be covered in First IA Test and remaining 40% to 50% of syllabus content
must be covered in Second IA Test
Questi on paper format

● Question Paper will comprise of a total of six questions each carrying 20 marks. Q.1 will be
compulsory and should cover maximum contents of the syllabus.
● Remaining questions will be mixed in nature (part (a) and part (b) of each quest ion must be
from different modules. For example, if Q.2 has part (a) from Module 3 then part (b) must be
from any other Module randomly selected from all the modules)
● A total of four questions needs to be answered.

Page 117

Course Code Course Name Theory Practical Tutorial Theory Oral Tutorial Total
IoTCSBCD
O8024 Cyber Security
laws & legal
aspects 03 -- -- 03 -- -- 03

Course
Code Course
Name Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End
Sem.
Exam Test1 Test 2 Avg. of 2
Tests
IoTCSBCD
O8024 Cyber
Security
laws & legal
aspects 20 20 20 80 -- -- -- 100
Course Objectives:

Sr.
No. Course Objectives
The course aims:
1 Understand the fundamental concepts and principles of cyber law and its relevance in the digital age.
2 Explore the legal implications of various cybercrimes and develop an understanding of the legal provisions
and penalties associated with them.
3 Gain knowledge of the legal aspects of cyber contracts, intellectual property rights, and their enforcement
in the digital domain.
4 Comprehend the legal frameworks, regulations, and compliance requirements related to information
security in various industries.
5 Examine the ethical and social implications of cyber activities and develop an ethical framework for
responsible digital behavior.
6 Analyze and evaluate the legal challenges in cybersecurity incidents and develop strategies for risk
management and incident response.
Course Outcomes:

Sr.
No. Course Outcomes Cognitive levels of
attainment as per
Bloom’s Taxonomy
On successful completion, of course, learner/student will be able to:
1 Demonstrate a comprehensive understanding of the principles, concepts,
and historical background of cyber law and its application in real -world
scenarios. L1, L2

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2 Identify and classify different types of cybercrimes, understand the legal
provisions and penalties associated with them, and effectively investigate
and prosecute cybercrimes. L1, L2
3 Evaluate the legal aspects of cyber contracts and intellectual property
rights, including their formation, validity, enforceability, and protection in
the digital era. L2, L3
4 Analyze and interpret the legal frameworks, regulations, and compliance
requirements re lated to information security standards in different
industries. L1, L2, L3
5 Recognize and assess the ethical and social implications of cyber activities,
and apply ethical frameworks and principles in cybersecurity practices. L1, L2
6 Develop a comprehensive understanding of the legal challenges in
cybersecurity incidents, including incident response, breach notification,
liability, and risk management. L2, L3

Prerequisite: Basic knowledge of computer networks, information technology, and cybersecurity, awareness of the ethical
implications of technology and digital activities, critical thinking and analytical skills for legal analysis and evaluation.


DETAILED SYLLABUS:

Sr.
No. Module Detailed Content Hou
rs CO
Mapping
0 Prerequisi
te Basic knowledge of computer networks, information technology, and
cybersecurity, awareness of the ethical implications of technology and
digital activities, critical thinking and analytical skills for legal analysis
and evaluation. 01
I Introducti
on to
Cyber
Law and
Legal
Aspects • What is Cyber Law?
• Need for Cyber Law
• Historical background and evolution of cyber law
• Key principles and concepts of cyber law
• Legal frameworks and regulations related to cybersecurity.
• Overview of international cyber law and its relevance
• Case studies illustrating the application of cyber law in real -
world scenarios.
Self-learning Topics: Comparative analysis of cyber laws in different
countries, Emerging trends and challenges in cyber law, Legal
implications of emerging technologies (e.g., artificial intelligence,
blockchain), Research and study of landmark cyber law cases 04 CO1
II Legal
Implicatio
ns of
Cyber
Crimes

• Introduction to Criminal Law
• Classification and types of cybercrimes (e.g., hacking, identity
theft, cyber fraud)
• Legal provisions and penalties for different
cybercrimes(Sections based on crimes)
• Investigation and prosecution of cybercrimes
• Jurisdictional Issues in cybercrime cases
• Role of digital evidence in cybercrime investigations
• Case studies on high -profile cybercrime incidents and their legal
implications
Self-learning Topics: Study of cybercrime laws in specific jurisdictions,
Analysis of cybercrime statistics and trends, Ethical considerations in
cybercrime investigations, Legal cha llenges in cross -border cybercrime
cases 08 CO2
III Cyber
Contracts
and
Intellectu• Legal aspects of cyber contracts, including formation, validity,
and enforceability
• Intellectual property rights in the digital domain (e.g., copyright,
trademarks, patents) 08 CO2

Page 119

al
Property
Rights • Protection and enforcement of intellectual property rights in the
digital era
• Digital rights management and anti -piracy measures
• Emerging issues in cyber contracts and intellectual property
rights (e.g., open -source software, digital c ontent licensing)
Self-learning Topics: Comparative analysis of intellectual property laws
in different countries, Study of legal cases involving cyber contracts and
intellectual property disputes, Examination of licensing agreements and
their legal implic ations.
IV Concepts
of
Cyberspa
ce &
Cyber
Law • Introduction to e -Commerce
• Contract & Security Aspects in Cyber Law
• Intellectual Property & Evidence Aspect in Cyber Law
• Criminal Aspects in Cyber Law
• Need for Indian Cyber Law
Self-learning Topics: Internet governance models and organizations
(e.g., ICANN, ITU), Cyber sovereignty and jurisdictional challenges,
Cybersecurity challenges in the digital era 07 CO4
V Informati
on
technolog
y Act • Introduction of Cybercrime
• Information Technology Act, 2000
• Offences under IT Act, 2000
• IT Act, 2008 & its Amendments
Self-learning Topics: Cybercrimes and their classification under the IT
Act, Investigation and prosecution of cybercrimes under the IT Act, Role
of digital evidence in cybercrime cases. 08 CO5
VI Informati
on
Security
Standard
Complian
ces • PCI Compliance
• ISO/IEC 27000
• North American Electric Reliability Corporation (NERC)
• Health Insurance Portability and Accountability Act (HIPAA)
• Sarbanes -Oxley Act (SOX)
Self-learning Topics: Audit and assessment processes for information
security compliance, Incident response and breach notification
procedures, Legal considerations in information security governance and
compliance 04 CO6

Text Books:

1. "Cyber Security & Cyber Laws" by Nilakshi Jain & Ramesh Menon ( Unit 4,5,6)
2. "Cyber Law Simplified" by Vivek Sood (Unit 1)
3. "Cyber Crime: Law and Practice" by Pavan Duggal (Unit 2)
4. "Intellectual Property Rights in Cyberspace" by Rajendra Kumar (Unit 3)
5. "Understanding Cyberspace Law" by George B. D elta and Jeffrey H. Matsuura (Unit 4)
6. "Information Technology Law and Practice" by Vakul Sharma (Unit 5)

References Books:

1. "Cyber Law: The Indian Perspective" by Karnika Seth
2. "Cyber Law and Crimes" by Dr. N.K. Aggarwal
3. "Cyber Law, Contracts, and Intellectual Property Rights" by A. Jayanthi
4. "Cyber Law: Indian and International Perspectives" by Yatindra Singh and Shantanu
Chattopadhyay
5. "Information Technology Law in India" by Vakul Sharma
6. "Information Security Management: Concepts and Practice" by P rashant Pathak and Sushil
Chandra

Online References:

1. Stanford Law School's Center for Internet and Society (https://cyberlaw.stanford.edu/)
2. Electronic Frontier Foundation (EFF) (https://www.eff.org/)

Page 120

3. National Institute of Standards and Technology (NIST) Cybersecurity Framework
(https://www.nist.gov/cyberframework)
4. International Association of Privacy Professionals (IAPP) (https://iapp.org/)
5. United Nations Commission on International Trade Law (UNCITRAL) - Electronic Commerce
and Information Technology
(https://uncitral.un.org/en/working_groups/6/electronic_commerce)

Assessment:
Internal Assessment (IA) for 20 marks:
● IA will consist of Two Compulsory Internal Assessment Tests. Approximately 40% to 50% of syllabus
content must be covered in First IA Test and remaining 40% to 50% of syllabus content must be covered in
Second IA Test
Question paper format
● Question Paper will comprise of a total of six questions each carrying 20 marks. Q.1 will be compulsory
and should cover maximum contents of the syllabus.
● Remaining questions will be mixed in nature (part (a) and part (b) of each question must be from different
modules. For example, if Q.2 has part (a) from Module 3 then part (b) must be from any other Module randomly
selected from all the module s)
● A total of four questions needs to be answered.

Page 121

Subject Code Subject Name Theory Practical Tutorial Theory Oral Tutorial Total
ILO8011 Project Management 03 -- -- 03 -- -- 03

Subject Code Subject Name Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End
Sem.
Exam Test1 Test
2 Avg. of
2 Tests
ILO8011 Project Management
20 20 20 80 -- -- -- 100

Course Objectives:
Sr. No. Course Objectives:
The course aims:
1 To familiarize the students with the use of a structured methodology/approach for each and every unique
project undertaken, including utilizing project management concepts, tools and techniques.
2 To appraise the students with the project management life cycle and make them knowledgeable about the
various phases from project initiation through closure

Course Outcomes:
Sr. No. Course Outcomes Cognitive levels of attainment as
per Bloom’s Taxonomy
On successful completion, of course, learner/student will be able to:
1 Apply selection criteria and select an appropriate project from
different options. L3

Page 122

2 Write work breakdown structure for a project and develop a schedule
based on it. L1, L6
3 Identify opportunities and threats to the project and decide
an approach to deal with them strategically. L1, L4
4 Use Earned value technique and determined & predict status of the
project. L3, L5
5 Capture lessons learned during project phases and document them for
future reference L3







Module
Detailed Contents
Hrs


01 Project Management Foundation:
Definition of a project, Project Vs Operations, Necessity of project management,
Triple constraints, Project life cycles (typical & atypical) Project phases and stage
gate process. Role of project manager. Negotiations and resolving conflicts. Project
management in various organization structures. PM knowledge
areas as per Project Management Institute (PMI).

5


02 Initiating Projects:
How to get a project started, selecting projects strategically, Project selection models
(Numeric /Scoring Models and Non -numeric models), Project portfolio process,
Project sponsor and creating charter; Project proposal. Effective project team, Stages
of team development & growth (forming, storming, nor ming &
performing), team dynamics.

6


03 Project Planning and Scheduling:
Work Breakdown structure (WBS) and linear responsibility chart, Interface
Coordination and concurrent engineering, Project cost estimation and budgeting, Top
down and bottoms up budgeting, Networking and Scheduling techniques. PERT,
CPM, GANTT chart. Introduction to Project Management
Information System (PMIS).

8


04 Planning Projects:
Crashing project time, Resource loading and leveling, Goldratt's critical chain,
Project Stakeholders and Communication plan.
Risk Management in projects: Risk management planning, Risk identification
and risk register. Qualitative and quantitative risk assessment, Probability and
impact matrix. Risk response strategies for positive an d negative risks

6
05
5.1 Executing Projects: Executing Projects:
Planning monitoring and controlling cycle. Information needs and reporting,
engaging with all stakeholders of the projects.
Team management, communication and project meetings.
Monitoring and Controlling Projects:
Earned Value Management techniques for measuring value of work completed; Using
milestones for measurement; change requests and scope creep. Project audit.
Project Contracting 8

Page 123

Project procurement management, contractin g and outsourcing,
06 Project Leadership and Ethics:
Introduction to project leadership, ethics in projects. Multicultural and virtual
projects.
Closing the Project:
Customer acceptance; Reasons of project termination, Various types of project
terminations (Extinction, Addition, Integration, Starvation), Process of project
termination, completing a final report; doing a lessons learned analysis;
acknowledging successes and failures; Project management templates and other
resources; Managing without authority; Areas of further study. 6





References:
1. Jack Meredith & Samuel Mantel, Project Management: A managerial approach, Wiley India,
7thEd.
2. A Guide to the Project Management Body of Knowledge (PMBOK® Guide), 5th Ed,Project
Management Institute PA,USA
3. Gido Clements, Project Management, CengageLearning.
4. Gopalan, Project Management, , WileyIndia
5. Dennis Lock, Project Management, Gower Publishing England, 9 thEd.

Assessment:
Internal:
Assessment consists of two tests out of which; one should be a compulsory class test and the other
is either a class test or assignment on live problems or course project.

End Semester Theory Examination:
Some guidelines for setting up the question paper. Minimum 80% syllabus should be covered in
question papers of end semester examination. In question paper weightage of each module will be
proportional to the number of respective lecture hours as mentioned in the syllabus.
1. Question paper will comprise of total six question
2. All question carry equal marks
3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from module 3 then
part (b) will be from any module other than module3)
4. Only Four questions need to be solved.

Page 124

Course Code Course
Name Theory Practical Tutorial Theory Oral Tutorial Total
ILO8012 Finance
Management 03 -- -- 03 -- -- 03

Course
Code Course Name Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End
Sem.
Exam Test
1 Test 2 Avg. of 2
Tests
ILO8012 Finance
Management 20 20 20 80 -- -- -- 100

Course Objectives:

Sr. No. Course Objectives:
The course aims:
1 Overview of Indian financial system, instruments and market
2 Basic concepts of value of money, returns and risks, corporate finance, working capital and its
management
3 Knowledge about sources of finance, capital structure, dividend policy

Course Outcomes:
Sr. No. Course Outcomes Cognitive levels of attainment
as per Bloom’s Taxonomy
On successful completion, of course, learner/student will be able to:
1 Understand Indian finance system and corporate finance L1
2 Discuss investment, finance as well as dividend decisions L2



Module
Detailed Contents
Hrs





01 Overview of Indian Financial System: Characteristics, Components and Functions of
Financial System.
Financial Instruments: Meaning, Characteristics and Classification of Basic Financial
Instruments — Equity Shares, Preference Shares, Bonds -Debentures, Certificates of
Deposit, and Treasury Bills.
Financial Markets: Meaning, Characteristics and Classification of Financial Markets —
Capital Market, Money Market and Foreign Currency Market Financial Institutions:
Meaning, Characteristics and Classification of Financial Institutions — Commercial
Banks, Investment -Merchant Banks and Stock



06

Page 125

Exchanges



02 Concepts of Returns and Risks: Measurement of Historical Returns and Expected
Returns of a Single Security and a Two -security Portfolio; Measurement of Historical
Risk and Expected Risk of a Single Security and a Two -security Portfolio.
Time Value of Money: Future Value of a Lump Sum, Ordinary Annuity, and Annuity
Due; Present Value of a Lump Sum, Ordinary Annuity, and Annuity
Due; Continuous Compounding and Continuous Discounting.


06



03 Overview of Corporate Finance: Objectives of Corporate Finance; Functions of
Corporate Finance —Investment Decision, Financing Decision, and Dividend Decision.
Financial Ratio Analysis: Overview of Financial Statements —Balance Sheet, Profit and
Loss Account, and Cash Flow Statement; Purpose of Financial Ratio Analysis; Liquidity
Ratios; Efficiency or Activity Ratios; Profitability Ratios.
Capital Structure Ratios; Stock Market Ratios; Lim itations of Ratio Analysis.


09


04 Capital Budgeting: Meaning and Importance of Capital Budgeting; Inputs for Capital
Budgeting Decisions; Investment Appraisal Criterion —Accounting Rate of Return,
Payback Period, Discounted Payback Period, Net Present Value ( NPV), Profitability
Index, Internal Rate of Return (IRR), and Modified
Internal Rate of Return (MIRR)
Working Capital Management: Concepts of Meaning Working Capital;
Importance of Working Capital Management; Factors Affecting an Entity’s Working
Capital Needs; Estimation of Working Capital Requirements; M anagement of Inventories;
Management of Receivables; and Management of Cash and Marketable Securities.

10



05 Sources of Finance: Long Term Sources —Equity, Debt, and Hybrids; Mezzanine
Finance; Sources of Short Term Finance —Trade Credit, Bank Finance, Commercial
Paper; Project Finance.
Capital Structure: Factors Affecting an Entity’s Capital Structure; Overview of Capital
Structure Theories and Approaches — Net Income Approach, Net Operating Income
Approach; Tradition al Approach, and Modigliani -Miller Approach. Relation between
Capital Structure and Corporate Value; Concept of
Optimal Capital Structure


05

06 Dividend Policy: Meaning and Importance of Dividend Policy; Factors Affecting an
Entity’s Dividend Decision; Overview of Dividend Policy Theories and Approaches —
Gordon’s Approach, Walter’s Approach, and Modigliani -
Miller Approach
03

Page 126

REFERENCES:

1. Fundamentals of Financial Management, 13th Edition (2015) by Eugene F. Brigham and Joel F.
Houston; Publisher: Cengage Publications, New Delhi.
2. Analysis for Financial Management, 10th Edition (2013) by Robert C. Higgins; Publishers:
McGraw Hill Education, New Delhi.
3. Indian Financial System, 9th Edition (2015) by M. Y. Khan; Publisher: M cGraw Hill
Education, New Delhi.
4. Financial Management, 11th Edition (2015) by I. M. Pandey; Publisher: S. Chand (G/L) &
Company Limited, New Delhi.

Assessment :

Internal:
Assessment consists of two tests out of which; one should be compulsory class test and the other is either a
class test or assignment on live problems or course project.

End Semester Theory Examination:
Some guidelines for setting up the question paper. Minimum 80% syllabus should be covered in question papers
of end semester examinatio n. In question paper weightage of each module will be proportional to number of
respective lecture hours as mentioned in the syllabus.
1. Question paper will comprise of total six question.
2. All question carry equal marks
3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from module 3 then part (b)
will be from any module other than module 3)
4. Only Four question need to be solved.

Page 127

Course
Code Course Name Theory Practical Tutorial Theory Oral Tutorial Total
ILO8013 Entrepreneurship
Development and
Management 03 -- -- 03 -- -- 03

Course
Code Course Name Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End
Sem.
Exam Tes
t1 Test 2 Avg. of 2
Tests
ILO8013 Entrepreneurship
Development and
Management 20 20 20 80 -- -- -- 100

Course Objectives:

Sr. No. Course Objectives:
The course aims:
1 To acquaint with entrepreneurship and management of business.
2 Understand Indian environment for entrepreneurship.
3 Idea of EDP,MSME.

Course Outcomes:
Sr. No. Course Outcomes Cognitive levels of attainment
as per Bloom’s Taxonomy
On successful completion, of course, learner/student will be able to:
1 Understand the concept of business plan and ownerships L1
2 Interpret key regulations and legal aspects of entrepreneurship in
India L5
3 Understand government policies for entrepreneurs. L1

Page 128

Module
Detailed Contents
Hrs


01 Overview Of Entrepreneurship: Definitions, Roles and Functions/Values of
Entrepreneurship, History of Entrepreneurship Development, Role of Entrepreneurship
in the National Economy, Functions of an Entrepreneur, Entrepreneurship and Forms of
Business Ownership
Role of Money and Capital Markets in Entrepreneurial Development:
Contribution of Government Agencies in Sourcing information for Entrepreneurship

04



02 Business Plans And Importance Of Capital To Entrepreneurship: Preliminary and
Marketing Plans, Management and Personnel, Start -up Costs and Financing as well as
Projected Financial Statements, Legal Section, Insurance, Suppliers and Risks,
Assumptions and Conclusion, Capital and its Importance to the Entrepreneur
Entrepreneurship And Business Development: Starting a New Busi ness,
Buying an Existing Business, New Product Development, Business Growth and the
Entrepreneur Law and its Relevance to Business Operations


09

03 Women’s Entrepreneurship Development, Social entrepreneurship -role and need, EDP
cell, role of sustainability and sustainable development for SMEs,
case studies, exercises 05


04 Indian Environment for Entrepreneurship: key regulations and legal aspects ,
MSMED Act 2006 and its implications, schemes and policies of the Ministry of MSME,
role and responsibilities of various government organisations, departments, banks etc.,
Role of State governments in terms of infrastructure developments and support etc.,
Public private partnerships, National Skill
development Mission, Credit Guarantee Fund, PMEGP, discussions, group exercises etc

08

05 Effective Management of Business: Issues and problems faced by micro and small
enterprises and effective management of M and S enterprises (risk
management, credit availability, technology innovation, supply chain
management, linkage with large industries), exercises, e-Marketing
08

06 Achieving Success In The Small Business: Stages of the small business life cycle, four
types of firm -level growth strategies, Options – harvesting or closing small business
Critical Success factors of small business
05

Page 129

REFERENCES:

1. Poornima Charantimath, Entrepreneurship development - Small Business Enterprise, Pearson
2. Education Robert D Hisrich, Michael P Peters, Dean A Shapherd, Entrepreneurship, latest edition, The
McGrawHill Company
3. Dr TN Chhabra, Entrepreneurship Development, Sun India Publications, New Delhi
4. Dr CN Prasad, Small and Medium Enterprises in Global Perspective, New century Publications, New
Delhi
5. Vasant Desai, Entrepreneurial development and management, Himalaya Publishing House
6. Maddhurima Lall, Shikah Sahai, Entrepreneurship, Excel Books
7. Rashmi Bansal, STAY hungry STAY foolish, CIIE, IIM Ahm edabad
8. Law and Practice relating to Micro, Small and Medium enterprises, Taxmann Publication Ltd.
9. Kurakto, Entrepreneurship - Principles and Practices, Thomson Publication
10. Laghu Udyog Samachar
11. www.msme.gov.in
12. www.dcmesme.gov.in
13. www.msmetraining.gov.in


Assessment :

Internal:
Assessment consists of two tests out of which; one should be compulsory class test and the other is either a
class test or assignment on live problems or course project.

End Semester Theory Examination:
Some guidelines for setting up the question paper. Minimum 80% syllabus should be covered in question papers
of end semester examination. In question paper weightage of each module will be proportional to number of
respective lecture hours as mention in the syllabus.
1. Question paper will comprise of total six question
2. All question carry equal marks
3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from module 3 then part (b)
will be from any module other than module 3)
4. Only Four question need to be solved.

Page 130

Course Code Course Name Theory Practical Tutorial Theory Oral Tutorial Total
ILO8014 Human
Resource
Management 03 -- -- 03 -- -- 03

Course
Code Course Name Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End
Sem.
Exam Test
1 Test 2 Avg. of 2
Tests
ILO8014 Human
Resource
Management 20 20 20 80 -- -- -- 100

Course Objectives:

Sr. No. Course Objectives:
The course aims:
1 To introduce the students with basic concepts, techniques and practices of human resource
management.
2 To provide an opportunity of learning Human resource management (HRM) processes, related
with the functions, and challenges in the emerging perspective of today's organizations.
3 To familiarize the students about the latest developments, trends & different aspects of HRM.
4 To acquaint the student with the importance of interpersonal & inter -group behavioral skills in
an organizational setting required for future stable engineers, leaders and managers.

Course Outcomes:
Sr.
No. Course Outcomes Cognitive levels of attainment as
per Bloom’s Taxonomy
On successful completion, of course, learner/student will be able to:
1 Understand the concepts, aspects, techniques and practices of human
resource management. L1
2 Understand the Human resource management (HRM) processes,
functions, changes and challenges in today’s emerging organizational
perspective. L1
3 Gain knowledge about the latest developments and trends inHRM. L1, L6
4 Apply the knowledge of behavioral skills learnt and integrate it
within an interpersonal and intergroup environment emerging as
future stable engineers and managers. L3

Page 131

Module
Detailed Contents
Hrs



01 Introduction to HR
• Human Resource Management - Concept, Scope and Importance, Interdisciplinary
Approach Relationship with other Sciences, Competencies of HR Manager, HRM
functions.
• Human resource development (HRD): changing role of HRM – Human resource Planning,
Technological change, Restructuring and rightsizing, Empowerment, TQM, Managing
ethical issues.


5






02 Organizational Behavior (OB)
• Introduction to OB Origin, Nature and Scope of Organizational Behavior, Relevance to
Organizational Effectiveness and Contemporary issues
• Personality: Meaning and Determinants of Personality, Personality development,
Personality Types, Assessment of Personality Traits for Increasing Self Awareness
• Perception: Attitude and Value, Effect of perception on Individual Decision -
making, Attitude and Behavior.
• Motivation: Theories of Motivation and their Applications for Behavioral
Change (Maslow, Herzberg, McGregor);
• Group Behavior and Group Dynamics: Work groups formal and informal groups and stages
of group development. Team Effectiveness: High performing teams, Team Roles, cross
functional and self -directed team.
• Case study





7

03 Organizational Structure &Design
• Structure, size, technology, Environment of organization; Organizational Roles & conflicts:
Concept of roles; role dynamics; role conflicts and stress.
• Leadership: Concepts and skills of leadership, Leadership and managerial roles,
Leadership styles and contemporary issues in leadership.
• Power and Politics: Sources and uses of power; Politics at workplace, Tactics and
strategies.
6



04 Human resource Planning
• Recruitment and Selection process, Job -enrichment, Empowerment - Job-Satisfaction,
employee morale.
• Performance Appraisal Systems: Traditional & modern methods, Performance
Counseling, Career Planning.
Training & Development: Identification of Training Needs, Training Methods


5



05 Emerging Trends in HR
• Organizational development; Business Process Re -engineering (BPR), BPR as a tool for
organizational development, managing processes & transformation in HR.
Organizational Change, Culture, Environment
• Cross Cultural Leadership and Decision Making : Cross Cultural Communication and
diversity at work , causes of diversity, managing.
diversity with special reference to handicapped, women and ageing people, intra company cultural
difference in emp loyee motivation.


6




06 HR & MIS
Need, purpose, objective and role of information system in HR, Applications in HRD in various
industries (e.g. manufacturing R&D, Public Transport, Hospitals, Hotels and service industries
Strategic HRM
Role of Strategic HRM in the modern business world, Concept of Strategy, Strategic
Management Process, Approaches to Strategic Decision Making; Strategic Intent – Corporate
Mission, Vision, Objectives and Goals
Labor Laws & Industrial Relations
Evolution of IR, IR issues in organizations, Overview of Labor Laws in India;
Industrial Disputes Act, Trade Unions Act, Shops and Establishments Act



10

Page 132

REFERENCES:

1. Stephen Robbins, Organizational Behavior, 16th Ed, 2013
2. V S P Rao, Human Resource Management, 3rd Ed, 2010, Excel publishing
3. Aswathapa, Human resource management: Text & cases, 6th edition, 2011
4. C. B. Mamoria and S V Gankar, Dynamics of Industrial Relations in India, 15th Ed, 2015, Himalaya
Publishing, 15thedition, 2015
5. P. Subba Rao, Essentials of Human Resource management and Industrial relations, 5th Ed, 2013,
Himalaya Publishing
6. Laurie Mullins, Management & Organizational Behavior, Latest Ed, 2016, Pearson Publications

Assessment :

Internal:
Assessment consists of two tests out of which; one should be compulsory class test and the other is either a
class test or assignment on live problems or course project.


End Semester Theory Examination:
Some guidelines for setting up the question paper. Minimum 80% syllabus should be covered in question papers
of end semester examination. In question paper weightage of each module will be proportional to number of
respective lecture hours as mentioned in the syllabus.
1. Question paper will comprise of total six question
2. All question carry equal marks
3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from module 3 then part (b)
will be from any module other than module 3)
4. Only Four question need to be solved.

Page 133

Course Code Course Name Theory Practical Tutorial Theory Oral Tutorial Total
ILO8015 Professional Ethics
and Corporate
Social
Responsibility
(CSR) 03 -- -- 03 -- -- 03

Course
Code Course Name Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End
Sem.
Exam Test
1 Test 2 Avg. of 2
Tests
ILO8015 Professional
Ethics and
Corporate Social
Responsibility
(CSR) 20 20 20 80 -- -- -- 100

Course Objectives:
Sr. No. Course Objectives:
The course aims:
1 To understand professional ethics in business
2 To recognize corporate social responsibility

Course Outcomes:
Sr. No. Course Outcomes Cognitive levels of attainment
as per Bloom’s Taxonomy
On successful completion, of course, learner/student will be able to:
1 Understand rights and duties of business L1
2 Distinguish different aspects of corporate social responsibility L2, L4
3 Demonstrate professional ethics L3
4 Understand legal aspects of corporate social responsibility L1





Module
Detailed Contents

Hrs

Page 134

01 Professional Ethics and Business: The Nature of Business Ethics; Ethical
Issues in Business; Moral Responsibility and Blame; Utilitarianism: Weighing
Social Costs and Benefits; Rights and Duties of Business 04


02 Professional Ethics in the Marketplace: Perfect Competition; Monopoly
Competition; Oligopolistic Competition; Oligopolies and Public Policy
Professional Ethics and the Environment: Dimensions of Pollution and
Resource Depletion; Ethics of Pollution Control; Ethics of Conserving
Depletable Resources

08


03 Professional Ethics of Consumer Protection: Markets and Consumer Protection;
Contract View of Business Firm’s Duties to Consumers; Due Care Theory;
Advertising Ethics; Consumer Privacy
Professional Ethics of Job Discrimination: Nature of Job Discrimination.
Extent of Discrimination; Reservation of Jobs.

06

04 Introduction to Corporate Social Responsibility: Potential Business Benefits —
Triple bottom line, Human resources, Risk management, Supplier relations;
Criticisms and concerns —Nature of business; Motives; Misdirection.
Trajectory of Corporate Social Respons ibility in India
05

05 Corporate Social Responsibility: Articulation of Gandhian Trusteeship
Corporate Social Responsibility and Small and Medium Enterprises (SMEs) in
India, Corporate Social Responsibility and Public -Private Partnership (PPP)in
India
08

06 Corporate Social Responsibility in Globalizing India: Corporate Social
Responsibility Voluntary Guidelines, 2009 issued by the Ministry of Corporate
Affairs, Government of India, Legal Aspects of Corporate Social
Responsibility —Companies Act, 2013.
08



References:

1. Business Ethics: Texts and Cases from the Indian Perspective (2013) by Ananda Das Gupta;
Publisher:Springer.
2. Corporate Social Responsibility: Readings and Cases in a Global Context (2007) by Andrew
Crane, Dirk Matten, Laura Spence; Publisher:Routledge.
3. Business Ethics: Concepts and Cases, 7th Edition (2011) by Manuel G. Velasquez; Publisher:
Pearson, NewDelhi.
4. Corporate Social Responsibility in India (2015) by BidyutChakrabarty, Routledge, NewDelhi.



Assessment:
Internal:
Assessment consists of two tests out of which; one should be a compulsory class test and the other
is either a class test or assignment on liv e problems or course project.
End Semester Theory Examination:
Some guidelines for setting up the question paper. Minimum 80% syllabus should be covered in
question papers of end semester examination. In question, paper weightage of each module will
be pro portional to the number of respective lecture hours as mentioned in the syllabus.
1. Question paper will comprise of total six question
2. All question carry equal marks
3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from mo dule 3 then
part (b) will be from any module other than module3)
4. Only Four questions need to be solved.

Page 135

Course Code Course Name Theory Practical Tutorial Theory Oral Tutorial Total
ILO8016 Research
Methodology 03 -- -- 03 -- -- 03

Course
Code Course Name Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End Sem.
Exam Test1 Test 2 Avg. of 2
Tests
ILO8016 Research
Methodology 20 20 20 80 -- -- -- 100

Course Objectives:

Sr. No. Course Objectives:
The course aims:
1 To understand Research and Research Process
2 To acquaint students with identifying problems for research and develop research strategies
3 To familiarize students with the techniques of data collection, analysis of data and interpretation

Course Outcomes:
Sr. No. Course Outcomes Cognitive levels of attainment as
per Bloom’s Taxonomy
On successful completion, of course, learner/student will be able to:
1 Prepare a preliminary research design for projects in their subject
matter areas L3
2 Accurately collect, analyze and report data L4
3 Present complex data or situations clearly L3
4 Review and analyze research findings L1, L4

Page 136

Module
Detailed Contents
Hrs



01 Introduction and Basic Research Concepts
Research – Definition; Concept of Construct, Postulate, Proposition, Thesis,
Hypothesis, Law, Principle. Research methods vs Methodology
Need of Research in Business and Social Sciences, Objectives of Research
Issues and Problems in Research
Characteristics of Research: Systematic , Valid, Verifiable, Empirical and Critical


09


02 Types of Research
Basic Research
Applied Research
Descriptive Research
Analytical Research
Empirical Research
2.6 Qualitative and Quantitative Approaches

07

03 Research Design and Sample Design
Research Design – Meaning, Types and Significance
Sample Design – Meaning and Significance Essentials of a good sampling
Stages in Sample Design Sampling methods/techniques Sampling Errors
07





04 Research Methodology
4.1 Meaning of Research Methodology
4.2. Stages in Scientific Research Process:
a. Identification and Selection of Research Problem
b. Formulation of Research Problem
c. Review of Literature
d. Formulation of Hypothesis
e. Formulation of research Design
f. Sample Design
g. Data Collection
h. Data Analysis
i. Hypothesis testing and Interpretation of Data
j. Preparation of Research Report




08

05 Formulating Research Problem
5.1 Considerations: Relevance, Interest, Data Availability, Choice of data,
Analysis of data, Generalization and Interpretation of analysis
04

06 Outcome of Research
Preparation of the report on conclusion reached.
Validity Testing & Ethical Issues
Suggestions and Recommendation
04

Page 137

References:

1. Dawson, Catherine, 2002, Practical Research Methods, New Delhi, UBS Publishers
Distributors.
2. Kothari, C.R.,1985, Research Methodology -Methods and Techniques, New Delhi, Wiley
EasternLimited.
3. Kumar, Ranjit, 2005, Research Methodology -A Step -by-Step Guide for Beginners, (2nded),
Singapore, Pearson Education

Assessment:
Internal:
Assessment consists of two tests out of which; one should be a compulsory class test and the other is
either a class test or assignment on live problems or course project.
End Semester Theory Examination:
Some guidelines for setting up the question paper. Minimum 80% syllabus should be covered in
question papers of end semester examination. In question, paper weightage of each module will be
proportional to the number of respective lecture hours as mentione d in the syllabus.
1. Question paper will comprise of total six question
2. All question carry equal marks
3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from module 3 then part
(b) will be from any module other than module3 )
4. Only Four questions need to be solved.

Page 138

Course Code Course Name Theory Practical Tutorial Theory Oral Tutorial Total
ILO8017 IPR and
Patenting 03 -- -- 03 -- -- 03

Course Code Course
Name Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End
Sem.
Exam Test
1 Test 2 Avg. of 2
Tests
ILO8017 IPR and
Patenting 20 20 20 80 -- -- -- 100

Course Objectives:

Sr. No. Course Objectives:
The course aims:
1 To understand intellectual property rights protection system
2 To promote the knowledge of Intellectual Property Laws of India as well as international treaty
procedures
3 To get acquaintance with Patent search and patent filing procedure and applications

Course Outcomes:
Sr. No. Course Outcomes Cognitive levels of attainment
as per Bloom’s Taxonomy
On successful completion, of course, learner/student will be able to:
1 Understand Intellectual Property assets L1
2 Support individuals and organizations in capacity building L5
3 Work for development, promotion, protection, compliance, and
enforcement of Intellectual Property and Patenting L6

Page 139

Module
Detailed Contents
Hr



01 Introduction to Intellectual Property Rights (IPR) : Meaning of IPR,
Different category of IPR instruments - Patents, Trademarks, Copyrights,
Industrial Designs, Plant variety protection, Geographical indications, Transfer
of technology.
Importance of IPR in Modern Global Economic Environment: Theories of
IPR, Philosophical aspects of IPR laws, Need for IPR, IPR as an instrument of
development


05



02 Enforcement of Intellectual Property Rights: Introduction, Magnitude of
problem, Factors that create and sustain counterfeiting/piracy, international
agreements, international organizations (e.g. WIPO, WTO) active in IPR
enforcement
Indian Scenario of IPR: Introduction, History of IPR in India, Overview of IP
laws in India, Indian IPR, Administrative Machinery, Major international
treaties signed by India, Procedure for submitting patent and Enforcement of
IPR at
national level etc.


07
03 Emerging Issues in IPR: Challenges for IP in digital economy, e -commerce,
human genome, biodiversity and traditional knowledge etc. 05


04 Basics of Patents: Definition of Patents, Conditions of patentability, Patentable
and non -patentable inventions, Types of patent applications (e.g. Patent of
addition etc), Process Patent and Product Patent, Precautions while patenting,
Patent specification Patent claims, Disclosures and non -disclosures, Patent
rights
and infringement, Method of getting a patent

07

05 Patent Rules: Indian patent act, European scenario, US scenario, Australia
scenario, Japan scenario, Chinese scenario, Multilateral treaties where India is
a
member (TRIPS agreement, Paris convention etc.)
08

06 Procedure for Filing a Patent (National and International): Legislation and
Salient Features, Patent Search, Drafting and Filing Patent Applications,
Processing of patent, Patent Litigation, Patent Publication etc, Time frame and
cost, Patent Licensing, Patent Infringement
Patent databases: Important websites, Searching international databases
07

Page 140

References:

1. Rajkumar S. Adukia, 2007, A Handbook on Laws Relating to Intellectual Property Rights in
India, The Institute of Chartered Accountants ofIndia
2. Keayla B K, Patent system and related issues at a glance, Published by National Working
Group on PatentLaws
3. T Sengupta, 2011, Intellectual Property Law in India, Kluwer LawInternational
4. Tzen Wong and Graham Dutfield, 2010, Intellectual Property and Human Develop ment:
Current Trends and Future Scenario, Cambridge UniversityPress
5. Cornish, William Rodolph & Llewelyn, David. 2010, Intellectual Property: Patents,
Copyrights, Trade Marks and Allied Right, 7th Edition, Sweet &Maxwell
6. LousHarns, 2012, The enforcement of Intellactual Property Rights: A Case Book, 3rd Edition,
WIPO
7. Prabhuddha Ganguli, 2012, Intellectual Property Rights, 1st Edition,TMH
8. R Radha Krishnan & S Balasubramanian, 2012, Intellectual Property Rights, 1st Edition,
Excel Books
9. M Ashok Kumar and mohdIq bal Ali, 2 -11, Intellectual Property Rights, 2nd Edition, Serial
Publications
10. Kompal Bansal and Praishit Bansal, 2012, Fundamentals of IPR for Engineers, 1st Edition,
BS Publications
11. Entrepreneurship Development and IPR Unit, BITS Pilani, 2007, A Manual on Intellectual
PropertyRights,
12. Mathew Y Maa, 2009, Fundamentals of Patenting and Licensing for Scientists and
Engineers, World Scientific PublishingCompany
13. N S Rathore, S M Mathur, Priti Mathur, Anshul Rathi , IPR: Drafting,Interpretation of Patent
Specifications and Claims , New India PublishingAgency
14. Vivien Irish, 2005, Intellectual Property Rights forEngineers,IET
15. Howard B Rockman, 2004, Intellectual Property Law for Engineers and scientists, Wiley -
IEEE Press

Assessment:

Internal:
Assessment consists of two tests out of which; one should be a compulsory class test and the other is
either a class test or assignment on live problems or course project.
End Semester Theory Examination:
Some guidelines for setting up the question paper. Min imum 80% syllabus should be covered in question
papers of end semester examination. In question, paper weightage of each module will be
proportional to the number of respective lecture hours as mentioned in the syllabus.
1. Question paper will comprise of total six question
2. All question carry equal marks
3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from module 3 then part
(b) will be from any module other than module3)
4. Only Four questions need to be solved.

Page 141

Course Objectives:

Sr. No. Course Objectives:
The course aims:
1 To familiarize with digital business concept
2 To acquaint with E-commerce
3 To give insights into E-business and its strategies
Course Outcomes:
Sr.
No. Course Outcomes Cognitive levels of attainment as
per Bloom’s Taxonomy
On successful completion, of course, learner/student will be able to:
1 Identify drivers of digital business L1, L4
2 Illustrate various approaches and techniques for E -business and
management L3, L4
3 Prepare E -business plan L3


Course
Code Course Name Theory Practical Tutorial Theory Oral Tutorial Total
ILO8018 Digital
Business
Management 03 -- -- 03 -- -- 03
Course
Code Course Name Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End
Sem.
Exam Test1 Test 2 Avg. of 2
Tests
ILO8018 Digital Business
Management 20 20 20 80 -- -- -- 100

Page 142

Module Detailed content Hours





1 Introduction to Digital Business -

Introduction, Background and current status, E -market places, structures,
mechanisms, economics and impacts
Difference between physical economy and digital economy,

Drivers of digital business - Big Data & Analytics, Mobile, Cloud Computing,
Social media, BYOD, and Internet of Things(digitally intelligent
machines/services)
Opportunities and Challenges in Digital Business,




09







2 Overview of E -Commerce

E-Commerce - Meaning, Retailing in e-commerce -products and services, consumer
behavior, market research and advertisement.
B2B-E-commerce -selling and buying in private e -markets, public B2B exchanges
and support services, e -supply chains, Collaborative Commerce, Intra business EC
and Cor porate portals.
Other E -C models and applications, innovative EC System -From E - government
and learning to C2C, mobile commerce and pervasive computing.
EC Strategy and Implementation -EC strategy and global EC, Economics and
Justification of EC, Using Affiliate marketing to promote your e- commerce
business, Launching a successful online business and EC project, Legal, Ethics and
Societal impacts of EC






06

3 Digital Business Support services : ERP as e –business backbone, knowledge Tope
Apps, Information and referral system
Application Development: Building Digital business Applications and
Infrastructure
06
4 Managing E -Business -Managing Knowledge, Management skills for e -
business, Managing Risks in e –business

Security Threats to e -business -Security Overview, Electronic Commerce Threats,
Encryption, Cryptography, Public Key and Private Key Cryptography, Digital
Signatures, Digital Certificates, Security Protocols over Public Networks: HTTP,
SSL, Firewall as Security Control, Public Key Infrastructure (PKI) for Security,
Prominent Cryptographic Applications. 06


5 E-Business Strategy -E-business Strategic formulation - Analysis of
Company’s Internal and external environment, Selection of strategy, E -business
strategy into Action, challenges and E -Transition (Process of Digital Transformation)

04
6 Materializing e -business: From Idea to Realization -Business plan
preparation
Case Studies and presentations
08

Page 143

References:

1. A textbook on E -commerce , Er Arunrajan Mishra, Dr W K Sarwade,Neha Publishers &
Distributors, 2011
2. E-commerce from vision to fulfilment, Elias M. Awad, PHI -Restricted, 2002
3. Digital Business and E -Commerce Management, 6th Ed, Dave Chaffey, Pearson, August 2014
4. Introduction to E-business -Management and Strategy, Colin Combe, ELSVIER, 2006
5. Digital Business Concepts and Strategy, Eloise Coupey, 2nd Edition, Pearson
6. Trend and Challenges in Digital Business Innovation, VinocenzoMorabito, Springer
7. Digital Business Discourse Erika Darics, April 2015, Palgrave Macmillan
8. E-Governance -Challenges and Opportunities in : Proceedings in 2nd International Conference
theory and practice of Electronic Governance
9. Perspectives the Digital Enterprise –A framework for Transformation, TCS consulting journal
Vol.5
10. Measuring Digital Economy -A new perspective -DOI: 10.1787/9789264221796 -enOECD
Publishin g

Assessment :

Internal:
Assessment consists of two tests out of which; one should be compulsory class test and the other is
either a class test or at least 6 assignment on complete syllabus or course project.



End Semester Theory Examination:
Some guidelines for setting up the question paper. Minimum 80% syllabus should be covered in question
papers of end semester examination. In question paper weightage of each module will be proportional
to number of respective lecture hours as mention in th e syllabus.
1. Question paper will comprise of total six question
2. All question carry equal marks
3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from module 3 then
part (b) will be from any module other than module 3)
4. Only Four question need to be solved.

Page 144

Course Code Course Name Theory Practical Tutorial Theory Oral Tutorial Total
ILO8019 Environmental
Management 03 -- -- 03 -- -- 03

Course
Code Course Name Examination Scheme
Theory Marks
Term
Work Practical Oral Total Internal assessment End
Sem.
Exam Test1 Test 2 Avg. of 2
Tests
ILO8019 Environmental
Management 20 20 20 80 -- -- -- 100

Course Objectives:

Sr. No. Course Objectives:
The course aims:
1 Understand and identify environmental issues relevant to India and global concerns
2 Learn concepts of ecology
3 Familiarize environment related legislations

Course Outcomes:
Sr.
No. Course Outcomes Cognitive levels of attainment as per
Bloom’s Taxonomy
On successful completion, of course, learner/student will be able to:
1 Understand the concept of environmental management L1
2 Understand ecosystem and interdependence, food chain etc. L1
3 Understand and interpret environment related legislations L1, L5

Page 145

Module
Detailed Contents
Hrs

01 Introduction and Definition of Environment: Significance of Environment Management
for contemporary managers, Career opportunities. Environmental issues relevant to India,
Sustainable Development, The Energy scenario.
10

02 Global Environmental concerns: Global Warming, Acid Rain, Ozone Depletion,
Hazardous Wastes, Endangered life -species, Loss of Biodiversity, Industrial/Man -made
disasters, Atomic/Biomedical hazards, etc.
06
03 Concepts of Ecology : Ecosystems and interdependence between living organisms,
habitats, limiting factors, carrying capacity, food chain, etc. 05

04 Scope of Environment Management, Role & functions of Government as a planning and
regulating agency. Environment Quality Management and Corporate Environmental
Responsibility
10
05 Total Quality Environmental Management, ISO -14000, EMS certification. 05

06 General overview of major legislations like Environment Protection Act, Air (P & CP)
Act, Water (P & CP) Act, Wildlife Protection Act, Forest Act, Factories Act, etc.
03


REFERENCES:

1. Environmental Management: Principles and Practice, C J Barrow, Routledge
Publishers London, 1999
2. A Handbook of Environmental Management Edited by Jon C. Lovett and David G. Ockwell,
Edward Elgar Publishing
3. Environmental Management, T V Ramachandra and Vijay Kulkarni, TERI Press
4. Indian Standard Environmental Management Systems — Requirements with Guidance For
Use, Bureau Of Indian Standards, February 2005
5. Environmental Management: An Indian Perspective, S N Chary and Vinod Vyasulu, Maclillan
India, 2000
6. Introduction to Environmental Management, Mary K Theodore and Louise Theodore,
CRC Press
7. Environment and Ecology, Majid Hussain, 3rd Ed. Access Publishing.2 015



Assessment :

Internal:
Assessment consists of two tests out of which; one should be compulsory class test and the other is
either a class test or assignment on live problems or course project.

End Semester Theory Examination:
Some guidelines for setting up the question paper. Minimum 80% syllabus should be covered in question
papers of end semester examination. In question paper weightage of each module will be proportional
to number of respective lecture hours as mentioned in the syllabus.
1. Question paper will comprise of total six question.
2. All question carry equal marks
3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from module 3 then
part (b) will be from any module other than module 3)
4. Only Four question need to be solved.