MScIT Part 2 Syllabus 2020 2021 Annexure I Syllabus Mumbai University

Page 1

Page 2

Copy to : -

1. The Director of Board of Student Development.,
2. The Deputy Registrar (Eligibility and Migration Section)
3. The Director of Students Welfare,
4. The Executive Secretary to the to the Vice -Chancellor,
5. The Pro -Vice-Chancellor
6. The Registrar and
7 The Assistant Registrar, Administrative sub -centers, Ratnagiri,
Thane & Kalyan, for information.

1. The Director of Board of Examinations and Evaluation
2. The Finance and Accounts Officers
3. Record Sectio n
4. Publications Section
5. The Deputy Registrar, Enrolment, Eligibility and Migration Section
6. The Deputy Registrar (Accounts Section), Vidyanagari
7. The Deputy Registrar, Affiliation Section
8. The Professor -cum- Director, Institute of Distance and Open Learning
Education,
9. The Director University Computer Center (IDE Building), Vidyanagari,
10. The Deputy Registrar (Special Cell),
11. The Deputy Registrar, (PRO)
12. The Deputy Registrar, Academic Authorities Unit (1 copies) and
13. The Assistant Registrar, Executive Authorities Unit

They are requested to treat this as action taken report on the
concerned resolution adopted by the Academic Council referred to in the
above circular and that on separate Action Taken Report will be sent in this
connection.
1. The Assistant Registrar Constituent Colleges Unit
2. BUCTU
3. The Deputy Accountant, Unit V
4. The In -charge Director, Centralize Computing Facility
5. The Receptionist
6. The Telephone Operator
7. The Secretary MUASA
8. The Superintendent, Post -Graduate Section
9. The Superintendent, Thesis Section

for information.

Page 3

i AC______________

Item No:__________

UNIVERSITY OF MUMBAI


Syllabus for Approval


Sr. No. Heading Particulars
1. Title of the Course M.Sc. (Information Technology) Part II
2. Eligibility for Admission
(Lateral Entry)
(Students who would like to
have additional degrees) Students who have completed MCA, M.Sc.
Computer Science / Mathematics / Statistics /
Physics / Electronics / Data Science, M.B.A. (I.T),
M.C.M., M.Tech (20% extr a seats to provided for
these students)
M.Sc IT from University of Mumbai (with
previous syllabus under General IT) or other
recognized Institutions who are willing to do
specialized degree
3. Passing Marks 40%
4. Ordinances / Regulations
(if, any) Existing ordinances and regulations.
5. Number of years /
Semesters Two years – Four Semesters
6. Level P.G. / U.G. /Diploma / Certificate
(Strike out which is not applicable)
7. Pattern Yearly / Semester, Choice Based
(Strike out which is not applicable)
8. Status New / Revised
9. To be implemented from
Academic year From the Academic Year 2020 – 2021

Date: April 17, 2020 Signature: _____________
Name of the BoS Chairperson / Dean : Dr. (Mrs.) R. Srivaramangai
(rsrimangai@udit.mu.ac.in )

Page 4

ii
Academic Council _________
Item No: _________















































UNIVERSITY OF MUMBAI

Syllabus for M.Sc. I.T. Part II
Semester III and IV
Programme: M.Sc.
Subject: Information Technology
CHOICE BASED(REVISED)
with effect from the academic year
2020 – 2021

Page 5

iii

Artificial Intelligence Track
Image Processing Track
Cloud Computing Track
Security Track
SEMESTER - III
Course Title
Course
Code Theory Credits Course
Code Practical Credits
PSIT301 Technical Writing
and Entrepreneurship
Development 4 PSIT3P1 Project Documentation
and Viva 2
Elective 1: Select Any one from the courses listed below along with corresponding practical
course
PSIT302a Applied Artificial
Intelligence
4 PSIT3P2a Applied Artificial
Intelligence Practical
2 PSIT302b Computer Vision PSIT3P2b Computer Vision
Practical
PSIT302c Cloud Application
Development PSIT3P2c Cloud Application
Development Practical
PSIT302d Security Breaches
and Countermeasures PSIT3P2d Security Breaches and
Countermeasures
Practical
Elective 2: Select Any one from the courses listed below along with corresponding practical
course
PSIT303a Machine Learning
4 PSIT3P3a Machine Learning
Practical
2 PSIT303b Biomedical Image
Processing PSIT3P3b Biomedical Image
Processing Practical
PSIT303c Cloud Management PSIT3P3c Cloud Management
Practical
PSIT303d Malware Analysis PSIT3P3d Malware Analysis
Practical
Elective 3: Select Any one from the courses listed below along with corresponding practical
course
PSIT304a Robotic Process
Automation
4 PSIT3P4a Robotic Process
Automation Practical
2 PSIT304b Virtual Reality and
Augmented Reality PSIT3P4b Virtual Reality and
Augmented Reality
Practical
PSIT304c Data Center
Technologies PSIT3P4c Data Center
Technologies Practical
PSIT304d Offensive Security PSIT3P4d Offensive Security
Practical
Total Theory Credits 16 Total Practical Credits 8
Total Credits for Semester III: 24

Page 6

iv
SEMESTER - IV
Course Title
Course
Code Theory Credits Course
Code Practical Credits
PSIT 401 Blockchain 4 PSIT4P1 2
Elective 1: Select Any one from the courses listed below along with corresponding practical
course
PSIT402a Natural Language
Processing
4 PSIT4P2a Natural Language
Processing Practical
2 PSIT402b Digital Image
Forensics PSIT4P2b Digital Image
Forensics Practical
PSIT402c Advanced IoT PSIT4P2c Advanced IoT
Practical
PSIT402d Cyber Forensics PSIT4P2d Cyber Forensics
Practical
Elective 2: Select Any one from the courses listed below along with corresponding practical
course
PSIT403a Deep Learning
4 PSIT4P3a Deep Learning
Practical
2 PSIT403b Remote Sensing PSIT4P3b Remote Sensing
Practical
PSIT403c Server Virtualization
on VMWare Platform PSIT4P3c Server Virtualization
on VMWare Platform
Practical
PSIT403d Security Operations
Center PSIT4P3d Security Operations
Center Practical
Elective 3: Select Any one from the courses listed below . Project Implementation and Viva is
compulsory
PSIT404a Human Computer
Interaction
4 PSIT4P4 Project
Implementation and
Viva 2 PSIT404b Advanced
Applications of
Image Processing
PSIT404c Storage as a Service
PSIT404d Information Security
Auditing
Total Theory Credits 16 Total Practical Credits 8
Total Credits for Semester IV: 24

If a student selects all 6 papers of Artificial Intelligence Track, he should be awarded the
degree M.Sc. (Information Technology), Artificial Intelligence Specialisation.
If a student selects all 6 papers of Image Processing Track, he should be awarded the degree
M.Sc. (Information Technology), Image Processing Specialisation.
If a student selects all 6 papers of Cloud Computing Track, he should be awarded the degree
M.Sc. (Information Technology), Cloud Computing Specialisation
If a student selects all 6 papers of Artificial Security Track, he should be awarded the degree
M.Sc. (Information Technology), Security Specialisation
All other stu dents will be awarded M.Sc. (Information Technology) degree.

Page 7

1 Table of Contents
PSIT301: Technical Writing and Entrepreneurship Development ................................ .... 3
PSIT3P1: Project Documentation and Viva ................................ ................................ .......... 7
PSIT302a: Applied Artificial Intelligence ................................ ................................ ............. 8
PSIT302b: Computer Vision ................................ ................................ ................................ . 10
PSIT302c: Cloud Application Development ................................ ................................ ........ 13
PSIT302d: Security Breaches and Countermeasures ................................ ......................... 16
PSIT303a: Machine Learning ................................ ................................ ............................... 19
PSIT303b: Biomedical Image Processing ................................ ................................ ............ 21
PSIT303c: Cloud Management ................................ ................................ ............................. 24
PSIT303d: Malware Analysis ................................ ................................ ............................... 32
PSIT304a: Robotic Process Automation ................................ ................................ .............. 35
PSIT304b: Virtual Reality and Augmented Reality ................................ ........................... 38
PSIT304c: Data Centre Technologies ................................ ................................ .................. 40
PSIT304d: Offensive Security ................................ ................................ ............................... 45
PSIT401: Blockchain ................................ ................................ ................................ ............. 51
PSIT402a: Natu ral Language Processing ................................ ................................ ............ 54
PSIT402b: Digital Image Forensics ................................ ................................ ...................... 57
PSIT402c: Advanced IoT ................................ ................................ ................................ ...... 59
PSIT402d: Cyber Forensics ................................ ................................ ................................ .. 61
PSIT403a: Deep Learning ................................ ................................ ................................ ..... 63
PSIT 403b: Remote Sensing ................................ ................................ ................................ ... 65
PSIT403c: Server Virtualization on VMWare Platform ................................ ................... 69
PSIT403d: Security Operations Centre ................................ ................................ ............... 75
PSIT404a: Human Computer Interaction ................................ ................................ ........... 80
PSIT404b: Advanced IoT ................................ ................................ ................................ ...... 82
PSIT404c: Storage as a Service ................................ ................................ ............................ 84
PSIT404d: Information Security Auditing ................................ ................................ .......... 90
PSIT4P4: Project Implementation and Viva ................................ ................................ ....... 93
Evaluation Scheme ................................ ................................ ................................ ................. 94
Internal Evaluation (40 Marks) ................................ ................................ ............................ 94
External Examination: (60 marks) ................................ ................................ ....................... 95
Practical Evaluation (50 marks) ................................ ................................ ........................... 95
Project Documentation and Viva Voce Evaluation ................................ ............................ 95
Project Implementation and Viva Voce Evaluation ................................ ........................... 95
Appendix – 1 ................................ ................................ ................................ ........................... 96

Page 8

2





















SEMESTER III

Page 9

3
PSIT301: Technical Writing and Entrepreneurship Development
M. Sc (Information Technology) Semester – III
Course Name: Technical Writing and Entrepreneurship
Development Course Code: PSIT301
Periods per week (1 Period is 60 minutes) 4
Credits 4
Hours Marks
Evaluation System Theory Examination 2½ 60
Internal -- 40

Course Objectives:

 This course aims to provide conceptual understanding of developing strong
foundation in general writing, including research proposal and reports.
 It covers the technological developing skills for writing Article, Blog, E -Book,
Commercial web Page design, Business Listing Press Releas e, E-Listing and Product
Description.
 This course aims to provide conceptual understanding of innovation and
entrepreneurship development.

Unit Details Lectures Outcome
I Introduction to Technical Communication:
What Is Technical Communication? The Challenges of
Producing Technical Communication, Characteristics of
a Technical Document , Measures of Excellence in
Technical Documents, Skills and Qualities Shared by
Successful Workplace Communicators, How
Communication Skills and Qualities Affect Your C areer?
Understanding Ethical and Legal Considerations: A
Brief Introduction to Ethics, Your Ethical Obligations,
Your Legal Obligations, The Role of Corporate Culture
in Ethical and Legal Conduct, Understanding Ethical and
Legal Issues Related to Social Me dia, Communicating
Ethically Across Cultures, Principles for Ethical
Communication Writing Technical Documents:
Planning, Drafting, Revising, Editing, Proofreading
Writing Collaboratively: Advantages and
Disadvantages of Collaboration, Managing Projects,
Conducting Meetings, Using Social Media and Other
Electronic Tools in Collaboration, Importance of Word
Press Website, Gender and Collaboration, Culture and
Collaboration . 12 CO1
II Introduction to Content Writing: Types of Content
(Article, Blog, E-Books, Press Release, Newsletters Etc),
Exploring Content Publication Channels. Distribution of
your content across various channels. Blog Creation:
Understand the psychology behind your web traffic, 12 CO2

Page 10

4 Creating killing landing pages which attract users, Us ing
Landing Page Creators, Setting up Accelerated Mobile
Pages, Identifying UI UX Experience of your website or
blog. Organizing Your Information: Understanding
Three Principles for Organizing Technical Information,
Understanding Conventional Organizationa l Patterns,
Emphasizing Important Information: Writing Clear,
Informative Titles, Writing Clear, Informative Headings,
Writing Clear Informative Lists, Writing Clear
Informative Paragraphs .
III Creating Graphics: The Functions of Graphics, The
Char acteristics of an Effective Graphic, Understanding
the Process of Creating Graphics, Using Color
Effectively, Choosing the Appropriate Kind of Graphic,
Creating Effective Graphics for Multicultural Readers.
Researching Your Subject: Understanding the
Differences Between Academic and Workplace
Research, Understanding the Research Process,
Conducting Secondary Research, Conducting Primary
Research, Research and Documentation: Literature
Reviews, Interviewing for Information, Documenting
Sources, Copyri ght, Paraphrasing, Questionnaires.
Report Components: Abstracts, Introductions, Tables of
Contents, Executive Summaries, Feasibility Reports,
Investigative Reports, Laboratory Reports, Test Reports,
Trip Reports, Trouble Reports 12 CO3
IV Writing Proposals: Understanding the Process of
Writing Proposals, The Logistics of Proposals, The
―Deliverables‖ of Proposals, Persuasion and Proposals,
Writing a Proposal, The Structure of the Proposal .
Writing Informational Reports: Understanding the
Process of Writing Informational Reports, Writing
Directives, Writing Field Reports, Writing Progress and
Status Reports, Writing Incident Reports, Writing
Meeting Minutes . Writing Recommendation Reports:
Understanding the Role of Recommendation Reports,
Using a Pro blem -Solving Model for Preparing
Recommendation Reports, Writing Recommendation
Reports . Reviewing, Evaluating, and Testing
Documents and Websites: Understanding Reviewing,
Evaluating, and Testing, Reviewing Documents and
Websites, Conducting Usability Eva luations, Conducting
Usability Tests, Using Internet tools to check writing
Quality, Duplicate Content Detector, What is
Plagiarism?, How to avoid writing plagiarism content?
Innovation management: an introduction: The
importance of innovation, Models of innovation,
Innovation as a management process . Market adoption
and technology diffusion: Time lag between innovation
and useable product, Innovation and the market , 12 CO4

Page 11

5 Innovation and market vision ,Analysing internet search
data to help adoption and forecas ting sales ,Innovative
new products and consumption patterns, Crowd sourcing
for new product ideas, Frugal innovation and ideas from
everywhere, Innovation diffusion theories .
V Managing innovation within firms: Organisations and
innovation, The d ilemma of innovation management,
Innovation dilemma in low technology sectors, Dynamic
capabilities, Managing uncertainty, Managing innovation
projects Operations and process innovation:
Operations management, The nature of design and
innovation in the con text of operations, Process design,
Process design and innovation
Managing intellectual property: Intellectual property,
Trade secrets, An introduction to patents, Trademarks,
Brand names, Copyright Management of research and
development: What is research and development?, R&D
management and the industrial context, R&D investment
and company success, Classifying R&D, R&D
management and its link with business strategy, Strategic
pressures on R&D, Which business to support and how?,
Allocation of funds to R&D , Level of R&D expenditure
Managing R&D projects: Successful technology
management, The changing nature of R&D management,
The acquisition of external technology, Effective R&D
management, The link with the product innovation
process, Evaluating R&D projec ts. 12 CO5

Books and References:
Sr. No. Title Author/s Publisher Edition Year
1. Technical
Communication
Mike Markel Bedford/St.
Martin's 11 2014
2. Innovation Management
and New Product
Development Paul Trott Pearson 06 2017
3. Handbook of Technical
Writing
Gerald J.
Alred , Charles T.
Brusaw , Walter E.
Oliu Bedford/St.
Martin's 09 2008
4. Technical Writing 101: A
Real-World Guide to
Planning and Writing
Technical Content Alan S. Pringle and
Sarah S. O'Keefe scriptorium 03 2009
5. Innovation and
Entrepreneurship Peter Drucker Harper
Business 03 2009

Page 12

6
Course Outcomes:
After completion of the course, a student should be able to:
CO1: Develop technical documents that meet the requirements with standard guidelines.
Understanding the essentials and hands -on learning about effective Website Development.
CO2: Write Better Quality Content Which Ranks faster at Search Engines. Build effective
Social Media Pages.
CO3: Evaluate the essentials parameters of effective Social Media Pages.
CO4: Understand importance of innovation and entrepreneurship.
CO5: Analyze research and development projects.

Page 13

7
PSIT3P1: Project Documentation and Viva
M. Sc (Information Technology) Semester – III
Course Name: Project Documentation and Viva Course Code: PSIT3P1
Periods per week (1 Period is 60 minutes) 4
Credits 2
Hours Marks
Evaluation System Practical Examination 2 50
Internal -- --

The learners are expected to develop a project beyond the undergraduate level. Normal web
sites, web applications, mobile apps are not expected. Preferably, the project should be from
the elective chosen by the learner at the post graduate level. In semester three. The learner is
supposed to prepare the synop sis and documentation. The same project has to be
implemented in Semester IV.
More details about the project is given is Appendix 1.

Page 14

8
PSIT302a: Applied Artificial Intelligence
M. Sc (Information Technology) Semester – III
Course Name: Applied Artificial Intelligence Course Code: PSIT302a
Periods per week (1 Period is 60 minutes) 4
Credits 4
Hours Marks
Evaluation System Theory Examination 2½ 60
Internal -- 40

Course Objectives:
- To explore the applied branches of artificial intelligence
- To enable the learner to understand applications of artificial intelligence
- To enable the student to solve the problem aligned with derived branches of
artificial intelligence.

Unit Details Lectures Outcome
I Review of AI: History, foundation and Applications
Expert System and Applications: Phases in Building Expert
System, Expert System Architecture, Expert System versus
Traditional Systems, Rule based Expert Systems, Blackboard
Systems, Truth Maintenance System, Application of Expert
Systems, Shells and Tools 12 CO1
II Probability Theory : joint probability , conditional
probability, Bayes’s theorem, probabilities in rules and facts
of rule based system, cumulative probabilities, rule based
system and Bayesian method
Fuzzy Sets and Fuzzy Logic: Fuzzy Sets, Fuzzy set
operations, Types of Mem ber ship Functions, Multivalued
Logic, Fuzzy Logic, Linguistic variables and Hedges, Fuzzy
propositions, inference rules for fuzzy propositions, fuzzy
systems, possibility theory and other enhancement to Logic 12 CO2
III Machine Learning Paradigms: Machine Learning systems,
supervised and un -supervised learning, inductive learning,
deductive learning, clustering, support vector machines, cased
based reasoning and learning.
Artificial Neural Networks: Artificial Neural Networks,
Single -Layer feedforw ard networks, multi -layer feed -forward
networks, radial basis function networks, design issues of
artificial neural networks and recurrent networks 12 CO3
IV Evolutionary Computation: Soft computing, genetic
algorithms, genetic programming concepts, evolu tionary
programming, swarm intelligence, ant colony paradigm,
particle swarm optimization and applications of evolutionary
algorithms.
Intelligent Agents: Agents vs software programs,
classification of agents, working of an agent, single agent and
multiage nt systems, performance evaluation, architecture, 12 CO4

Page 15

9 agent communication language, applications
V Advanced Knowledge Representation Techniques:
Conceptual dependency theory, script structures, CYC theory,
script structure, CYC theory, case grammars, semantic web.
Natural Language Processing:
Sentence Analysis phases, grammars and parsers, types of
parsers, semantic analysis, universal networking language,
dictionary 12 CO5

Books and References:
Sr. No. Title Author/s Publisher Edition Year
1. Artificial Intelligence Saroj Kaushik Cengage 1st 2019
2. Artificial Intelligence: A
Modern Approach A. Russel, Peter
Norvig 1st
3. Artificial Intelligence Elaine Rich,Kevin
Knight,Shivashankar
B. Nair Tata Mc -
Grawhill 3rd

M. Sc (Information Technology) Semester – III
Course Name: Artificial Intelligence Practical Course Code: PSIT3P2a
Periods per week (1 Period is 60 minutes) 4
Credits 2
Hours Marks
Evaluation System Practical Examination 2 50
Internal -- --

List of Practical:
10 practicals covering the entire syllabus must be performed. The detailed list of
practical will be circulated later in the official workshop.

Course Outcome s:

After completion of course the learner will:
CO1: be able to understand the fundamentals concepts of expert system and its applications.
CO2: be able to use probability and concept of fuzzy sets for solving AI based problems.
CO3: be able to understand the applications of Machine Learning. The learner ca n also apply
fuzzy system for solving problems.
CO4: learner will be able to apply to understand the applications of genetic algorithms in
different problems related to artificial intelligence.
CO5: A learner can use knowledge representation techniques i n natural language processing.

Page 16

10 PSIT302b: Computer Vision
M. Sc (Information Technology) Semester – III
Course Name: Computer Vision Course Code: PSIT302b
Periods per week (1 Period is 60 minutes) 4
Credits 4
Hours Marks
Evaluation System Theory Examination 2½ 60
Internal -- 40

Course Objectives:

 To develop the student's understanding of the issues involved in trying to define and
simulate perception.
 To familiarize the student with specific, well known computer vision methods,
algorithms and results.
 To provide the student additional experience in the analysis and evaluation of
complicated systems.
 To provide the student additional software development experience.
 To provide the student with paper and proposal writing experience .

Unit Details Lectures Outcome
I Introduction: What is computer vision?, A brief
history, Image formation, Geometric primitives and
transformations, Geometric primitives, D
transformations, D transformations, D rotations, D to D
projections, Lens distortions, Photometric image
formation, Lighting, R eflectance and shading, Optics,
The digital camera, Sampling and aliasing, Color
,Compression
Feature -based alignment : D and D feature -based
alignment, D alignment using least squares , Application:
Panography , Iterative algorithms , Robust least square s
and RANSAC , D alignment , Pose estimation , Linear
algorithms, Iterative algorithms , Application:
Augmented reality , Geometric intrinsic calibration,
Calibration patterns, Vanishing points , Application:
Single view metrology , Rotational motion ,Radi al
distortion 12 CO1
II Structure from motion : Triangulation, Two -frame
structure from motion , Projective (uncalibrated)
reconstruction, Self -calibration , Application: View
morphing , Factorization, Perspective and projective
factorization , Applicati on: Sparse D model extraction,
Bundle adjustment, Exploiting sparsity , Application:
Match move and augmented reality , Uncertainty and
ambiguities , Application: Reconstruction from Internet
photos , Constrained structure and motion , Line -based
technique s , Plane -based techniques 12 CO2

Page 17

11 Dense motion estimation : Translational alignment ,
Hierarchical motion estimation, Fourier -based alignment
, Incremental refinement , Parametric motion,
Application: Video stabilization, Learned motion models
, Spline -based motion, Application: Medical image
registration, Optical flow, Multi -frame motion estimation
,Application: Video denoising , Application: De -
interlacing , Layered motion, Application: Frame
interpolation, Transparent layers and reflections
III Image stitching : Motion models, Planar perspective
motion, Application: Whiteboard and document scanning
, Rotational panoramas , Gap closing , Application:
Video summarization and compression, Cylindrical and
spherical coordinates, Global alignment, Bund le
adjustment,Parallax removal , Recognizing panoramas,
Direct vsfeature -based alignment, Compositing ,
Choosing a compositing surface, Pixel selection and
weighting (de -ghosting) , Application:
Photomontage,Blending
Computational photography : Photometr ic calibration
,Radiometric response function ,Noise level estimation
,Vignetting ,Optical blur (spatial response) estimation
,High dynamic range imaging ,Tone mapping
,Application: Flash photograpy,Super -resolution and blur
removal,Color image demosaicin g ,Application:
Colorization,Image matting and compositing ,Blue
screen matting ,Natural image matting ,Optimization -
based matting ,Smoke, shadow, and flash matting ,Video
matting ,Texture analysis and synthesis ,Application:
Hole filling and inpainting ,A pplication: Non -
photorealistic rendering 12 CO3
IV Stereo correspondence
Epipolar geometry , Rectification ,Plane sweep , Sparse
correspondence , D curves and profiles , Dense
correspondence, Similarity measures , Local methods ,
Sub-pixel estimation and uncertainty , Application:
Stereo -based head tracking , Global optimization ,
Dynamic programming , Segmentation -based techniques,
Application: Z -keying and background replacement,
Multi -view stereo, Volumetric and D surface
reconstruction, Shape from silhouettes
3D reconstruction : Shape from X , Shape from
shading and photometric stereo, Shape from texture,
Shape from focus , Active rangefinding , Range data
merging , Application: Digital heritage , Surface
representations , Surface interpolation, Surface
simplification, Geometry images , Point -based
representations, Volumetric representations , Implicit
surfaces and level sets , Model -based reco nstruction,
Architecture, Heads and faces , Application: Facial 12 CO4

Page 18

12 animation , Whole body modeling and tracking
,Recovering texture maps and albedos , Estimating
BRDFs ,Application: D photography
V Image -based rendering : View interpolation, View -
dependent texture maps, Application: Photo Tourism ,
Layered depth images, Impostors, sprites, and layers,
Light fields and Lumigraphs , Unstructured Lumigraph,
Surface light fields, Application: Concentric mosaics,
Environment mattes, Higher -dimensional l ight fields ,
The modeling to rendering continuum, Video -based
rendering , Video -based animation, Video textures ,
Application: Animating pictures, D Video, Application:
Video -based walkthroughs
Recognition : Object detection, Face detection,
Pedestrian detection, Face recognition, Eigenfaces,
Active appearance and D shape models, Application:
Personal photo collections, Instance recognition,
Geometric alignment, Large databases, Application:
Location recognition, Category recognition, Bag of
words, Part -based models, Recognition with
segmentation, Application: Intelligent photo editing,
Context and scene understanding , Learning and large
image collections, Application: Image search,
Recognition databases and test sets 12 CO5

Books and References:
Sr. No. Title Author/s Publisher Edition Year
1. Computer Vision: Algorithms
and Applications Richard Szeliski Springer 1st
Edition 2010

M. Sc (Information Technology) Semester – III
Course Name: Computer Vision Practical Course Code: PSIT3P2b
Periods per week (1 Period is 60 minutes) 4
Credits 2
Hours Marks
Evaluation System Practical Examination 2 50
Internal -- --

List of Practical:
10 practicals covering the entire syllabus must be performed. The detailed list of
practical will be circulated later in the official workshop.

Course Outcomes:
After completion of the course, a student should be able to:
CO1: Understand the basics of computer vision
CO2: Understand and analyse various structure form motion and various estimates of Dense
Motion
CO3: Apply various motion models to images and understand computation photography
techniques

Page 19

13 CO4: Apply Epipolar geometry , Rectification and various other 3D correspondence and
Stereo reconstruction techniques
CO5: Understand image -based rendering and reconstruction
PSIT302c : Cloud Application Development
M. Sc (Information Technology) Semester – III
Course Name: Cloud Application Development Course Code: PSIT 302c
Periods per week (1 Period is 60 minutes) 4
Credits 4
Hours Marks
Evaluation System Theory Examination 2½ 60
Internal -- 40

Course Objectives:
 To develop and deploy Microservices for cloud
 To understand Kubernetes and deploy applications on Azure Kubernetes Service
 To understand DevOps for Azure
 To follow the DevOps practices for software development
 To build APIs for Azure and AWS


Unit Details Lectures Outcomes
I Implementing Microservices: Client to microservices
communication, Interservice communication, data
considerations, security, monitoring, microservices hosting
platform options.
Azure Service Fabric: Introduction, core concepts,
supported programming models, service fabric clusters,
develop and deploy applications of serv ice fabric.
Monitoring Azure Service Fabric Clusters: Azure
application, resource manager template, Adding
Application Monitoring to a Stateless Service Using
Application Insights, Cluster monitoring, Infrastructure
monitoring. 12 CO1
II Azure Kubernetes Service (AKS): Introduction to
kubernetes and AKS, AKS development tools, Deploy
applications on AKS.
Monitoring AKS: Monitoring, Azure monitor and
analytics, monitoring AKS clusters, native kubernetes
dashboard, Prometheus and Grafana.
Securing Microser vices: Authentication in microservices,
Implenting security using API gateway pattern, Creating
application using Ocrlot and securing APIs with Azure AD.
Database Design for Microservices: Data stores,
monolithic approach, Microservices approach, harnessin g
cloud computing, dataase options on MS Azure,
overcoming application development challenges.
Building Microservices on Azure Stack: Azure stack,
Offering IaaS, PaaS on -premises simplified, SaaS on Azure 12 CO2

Page 20

14 stack.
III .NET DevOps for Azure: DevOps in troduction, Problem
and solution.
Professional Grade DevOps Environment: The state of
DevOps, professional grade DevOps vision, DevOps
architecture, tools for professional DevOps environment,
DevOps centered application.
Tracking work: Process template, T ypes of work items,
Customizing the process, Working with the process.
Tracking code: Number of repositories, Git repository,
structure, branching pattern, Azure repos configuration, Git
and Azure. 12 CO3
IV Building the code: Structure of build, using builds with
.NET core and Azure pipelines,
Validating the code: Strategy for defect detection,
Implementing defect detection.
Release candidate creation: Designing release candidate
architecture, Azure artifacts workflow for rele ase
candidates,
Deploying the release: Designing deployment pipeline,
Implementing deployment in Azure pipelines.
Operating and monitoring release: Principles,
Architectures for observability, Jumpstarting observability. 12 CO4
V Introduction to APIs: Introduction, API economy, APIs in
public sector.
API Strategy and Architecture: API Strategy, API value
chain, API architecture, API management.
API Development: Considerations, Standards, kick -start
API development, team orientation.
API Gateways: API Ga teways in public cloud, Azure API
management, AWS API gateway.
API Security: Request -based security, Authentication and
authorization. 12 CO5

Books and References:
Sr. No. Title Author/s Publisher Edition Year
1. Building Microservices
Applications on Microsoft
Azure - Designing,
Developing, Deploying, and
Monitoring Harsh Chawla
Hemant Kathuria Apress -- 2019
2. .NET DevOps for Azure
A Developer’s Guide to
DevOps Architecture the
Right Way Jeffrey Palermo Apress -- 2019
3. Practical API Architecture
and Development with
Azure and AWS - Design
and Implementation of APIs
for the Cloud Thurupathan
Vijayakumar Apress -- 2018

Page 21

15 M. Sc (Information Technology) Semester – III
Course Name: Cloud Application Development
Practical Course Code: PSIT3P2c
Periods per week (1 Period is 60 minutes) 4
Credits 2
Hours Marks
Evaluation System Practical Examination 2 50
Internal -- --


List of Practical:
10 practical covering the entire syllabus must be performed. The detailed list of
practical will be circulated later in the official workshop.


Course Outcomes:
After completion of the course, a student should be able to:

CO01: Develop the Microservices for cloud and deploy them on Microsoft Azure.

CO02: Build and deploy services to Azure Kubernetes service.

CO03: Understand and build the DevOps way.

CO04: Thoroughly build the applications in the DevOps way.

CO05: Build the APIs for Microsoft Azure and AWS.

Page 22

16 PSIT302d : Security Breaches and Countermeasures
M. Sc (Information Technology) Semester – III
Course Name: Security Breaches and Countermeasures Course Code: PSIT302d
Periods per week (1 Period is 60 minutes) 4
Credits 4
Hours Marks
Evaluation System Theory Examination 2½ 60
Internal -- 40

Course Objectives:
 To get the insight of the security loopholes in every aspect of computing.
 To understand the threats and different types of attacks that can be launched on
computing systems.
 To know the countermeasures that can be taken to prevent attacks on computing systems.
 To test the software against the attacks.


Unit Details Lectures Outcome
I Introduction to Security Breaching : Overview of
Information Security, Threats and Attack vectors,
Concepts of Hacking – Ethical and Unethical,
Information Security Controls, Concepts of
penetration Testing, Information Security Laws and
Standards.
Evaluation Security of IT Organisation: Concepts,
Methodology, Tools, Countermeasures, Penetration
Testing.
Network Scanning: Concepts, Scanning beyond IDS
and firewalls, Tools, Banner Grabbing, Scanning
Techniques, Network Diagrams, penetration testing.
Enumeration: Concepts, Different types of
enumeration: Netbios, SNMP, LDAP, NTP, SMTP,
DNS, other enumeration techniques,
Countermeasure s, Penetration Testing 12 CO1
II Analysis of Vulnerability: Concepts, Assessment
Solutions, Scoring Systems, Assessment Tools,
Assessment Reports.
Breaching System Security: Concepts, Cracking
passwords, Escalating privileges, Executing
Applications, Hiding files, covering tracks,
penetration testing.
Threats due to malware: Concepts, Malware
Analysis, Trojan concepts, countermeasures, Virus
and worm concepts, anti -malware software,
penetration testing.
Network Sniffing: Concepts, countermeasures,
sniffing techniques, detection techniques, tools,
penetration testing. 12 CO2

Page 23

17 III Social Engineering: Concepts, Impersonation on
networking sites, Techniques, Identity theft, Insider
threats, countermeasures, Pen testing.
Denial of Service and Distributed Denial of service:
Concepts, techniques, botnets, attack tools,
countermeasures, protection tools, penetration testing.
Hijacking an active session: Concepts, tools,
application level session hijacking, countermeasures,
network level session hijacking, penetration testing.
Evasion of IDS, Firewalls and Honeypots:
Introduction and concepts, detecting honeypots,
evading IDS, IDS and Firewall evasion
countermeasures, evading firewalls, penetration
testing. 12 CO3
IV Compromis ing Web Servers: Concepts, attacks,
attack methodology, attack tools, countermeasures,
patch management, web server security tools,
penetration testing.
Compromising Web Applications: Concepts ,
threats, methods, tools, countermeasures, testing tools,
penet ration testing.
Performing SQL Injection: Concepts, types,
methodology, tools, techniques, countermeasures.
Compromising Wireless Networks: Concepts,
wireless encryption, threats, methodology, tools,
compromising Bluetooth, countermeasures, wireless
security tools, penetration testing. 12 CO4
V Compromising Mobile Platforms: Attack vectors,
Compromising Android OS, Compromising iOS,
Mobile spyware, Mobile Device Management, Mobile
security, penetration testing.
Compromising IoT: Concepts, attacks,
compromising methodology, tools, countermeasures,
penetration testing.
Cloud Security: Concepts, Security, threats, attacks,
tools, penetration testing.
Cryptography: Concepts, email encryption,
algorithms, disk encryption, tools, cryptanalysis,
Public key infrastructure, countermeasures. 12 CO5

Books and References:
Sr. No. Title Author/s Publisher Edition Year
1. CEHv10, Certified Ethical
Hacker Study Guide Ric Messier Sybex - Wiley - 2019
2. All in One, Certified
Ethical Hacker Matt Walker Tata McGraw
Hill - 2012
3. CEH V10: EC -Council
Certified Ethical Hacker
Complete Training Guide I.P. Specialist IPSPECIALIST - 2018

Page 24

18 M. Sc (Information Technology) Semester – III
Course Name: Security Breaches and Countermeasures
Practical Course Code: PSIT3P3d
Periods per week (1 Period is 60 minutes) 4
Credits 2
Hours Marks
Evaluation System Practical Examination 2 50
Internal -- -

List of Practical:
10 practicals covering the entire syllabus must be performed. The detailed list of
practical will be circulated later in the official workshop.

Course Outcome:
CO1: The student should be able to identify the different security breaches that can occur.
The student sho uld be able to evaluate the security of an organization and identify the
loopholes. The student should be able to perform enumeration and network scanning.

CO2: The student should be able to identify the vulnerability in the systems, breach the
security o f the system, identify the threats due to malware and sniff the network. The student
should be able to do the penetration testing to check the vulnerability of the system towards
malware and network sniffing.

CO3: The student should be able to perform soc ial engineering and educate people to be
careful from attacks due to social engineering, understand and launch DoS and DDoS attacks,
hijack and active session and evade IDS and Firewalls. This should help the students to make
the organization understand th e threats in their systems and build robust systems.

CO4: The student should be able to identify the vulnerabilities in the Web Servers, Web
Applications, perform SQL injection and get into the wireless networks. The student should
be able to help the organization aware about these vulnerabilities in their systems.

CO5: The student should be able to identify the vulnerabilities in the newer technologies like
mobiles, IoT and cloud computing. The student should be able to use different methods of
crypto graphy.

Page 25

19 PSIT303a : Machine Learning
M. Sc (Information Technology) Semester – III
Course Name: Machine Learning Course Code: PSIT303a
Periods per week (1 Period is 60 minutes) 4
Credits 4
Hours Marks
Evaluation System Theory Examination 2½ 60
Internal -- 40

Course Objectives:
 Understanding Human learning aspects.
 Understanding primitives in learning process by computer.
 Understanding nature of problems solved with Machine Learning

Unit Details Lectures Outcome
I Introduction: Machine learning, Examples of Machine
Learning Problems, Structure of Learning, learning versus
Designing, Training versus Testing, Characteristics of
Machine learning tasks, Predictive and descriptive tasks,
Machine learning Models: Geometric Models, Logi cal
Models, Probabilistic Models. Features: Feature types,
Feature Construction and Transformation, Feature
Selection. 12
CO1
II Classification and Regression: Classification: Binary
Classification - Assessing Classification performance,
Class probability Estimation Assessing class probability
Estimates, Multiclass Classification. Regression :
Assessing performance of Regression - Error measures,
Overfitting - Catalysts for Overfitting, Case study of
Polynomial Regression. Theory of Generalization:
Effective number of hypothesis, Bounding the Growth
function, VC Dimensions, Regularization theory. 12 CO2
III Linear Models: Least Squares method, Multivariate
Linear Regression, Regularized Regression, Using Least
Square regression for Classification. Perceptron, Support
Vector Machines, Soft Margin SVM, Obtaining
probabilities from Linear classifiers, Kernel methods for
non-Linearity. 12 CO2
CO3
IV Logic Based and Algebraic Model: Distance Based
Models: Neighbours and Examples, Nearest Neighbours
Classification, Distance based clustering -K means
Algorithm, Hierarchical clustering, Rule Based Models:
Rule learning for subgroup discovery, Association rule
mining. Tree Based Models: Decision Trees, Ranking
and Probability estimation Trees, Regressi on trees,
Clustering Trees.

12 CO2
CO3
CO4

Page 26

20 V Probabilistic Model:
Normal Distribution and Its Geometric Interpretations,
Naïve Bayes Classifier, Discriminative learning with
Maximum likelihood, Probabilistic Models with Hidden
variables: Estimation -Maximization Methods, Gaussian
Mixtures, and Compression based Models.
Trends In Machine Learning : Model and Symbols -
Bagging and Boosting, Multitask learning, Online learning
and Sequence Prediction, Data Streams and Active
Learning, Deep Lear ning, Reinforcement Learning. 12 CO5

Books and References:
Sr. No. Title Author/s Publisher Edition Year
1. Machine Learning: The Art
and Science of Algorithms
that Make Sense of Data Peter Flach Cambridge
University
Press 2012
2. Introduction to Statistical
Machine Learning with
Applications in R Hastie, Tibshirani,
Friedman Springer 2nd 2012
3. Introduction to Machine
Learning Ethem Alpaydin PHI 2nd 2013

M. Sc (Information Technology) Semester – III
Course Name: Machine Learning Practical Course Code: PSIT 3P3a
Periods per week (1 Period is 60 minutes) 4
Credits 2
Hours Marks
Evaluation System Practical Examination 2 50
Internal -- -

List of Practical:
10 practicals covering the entire syllabus must be performed. The detailed list of
practical will be circulated later in the official workshop.

Course Outcomes:
After completion of the course, a student should be able to:
CO1 : Understand the key issues in Machine Learning and its associated applications in
intelligent business and scientific computing.
CO2 : Acquire the knowledge about classification and regression techniques where a learner
will be able to explore his skill t o generate data base knowledge using the prescribed
techniques.
CO3 : Understand and implement the techniques for extracting the knowledge using machine
learning methods.
CO4 : Achieve adequate perspectives of big data analytics in various applications like
recommender systems, social media applications etc.
CO5 : Understand the statistical approach related to machine learning. He will also Apply the
algorithms to a real -world problem, optimize the models learned and report on the expected
accuracy that can b e achieved by applying the models.

Page 27

21 PSIT303b: Biomedical Image Processing
M. Sc (Information Technology) Semester – III
Course Name: Biomedical Image Processing Course Code: PSIT303b
Periods per week (1 Period is 60 minutes) 4
Credits 4
Hours Marks
Evaluation System Theory Examination 2½ 60
Internal -- 40

Course Objectives:

 To design intelligent systems that can analyze biomedical images.
 To understand different scientific approaches in biomedical image processing.
 To understand the structure of biomedical images and how to correlate it with
different biological data.
 To design systems to identify different physical conditions on the basis of biomedical
data.

Unit Details Lectures Outcome
I Introduction: Biosignals, Biosignal Measurement
Systems, Transducers, Amplifier/Detector, Analog
Signal Processing and Filters, ADC Conversion, Data
Banks
Bio signal Measurements, Noise, and Analysis:
Biosignals, Noise, Signal Analysis: Data Functions and
Transforms
Spectral Analysis: Class ical Methods : Fourier Series
Analysis, Power Spectrum, Spectral Averaging:
Welch’s Method
Noise Reduction and Digital Filters : Noise
Reduction, Noise Reduction through Ensemble
Averaging, Z -Transform, Finite Impulse Response
Filters, Infinite Impulse Res ponse Filters 12 CO1
II Modern Spectral Analysis: The Search for
Narrowband Signals: Parametric Methods,
Nonparametric Analysis: Eigen analysis Frequency
Estimation
Time Frequency Analysis: Basic Approaches, The
Short -Term Fourier Transform: The Spectrogram, The
Wigner Ville Distribution: A Special Case of Cohen’s
Class, Cohen’s Class Distributions
Wavelet Analysis: Continuous Wavelet Transform,
Discrete Wavelet Transform, Feature Detection:
Wavelet Packets
Optimal and Adaptive Filters: Optimal Si gnal
Processing: Wiener Filters, Adaptive Signal Processing,
Phase -Sensitive Detection
12 CO2

Page 28

22 III Multivariate Analyses: Principal Component Analysis
and Independent Component Analysis : Linear
Transformations, Principal Component Analysis,
Independent Component Analysis
Chaos and Nonlinear Dynamics : Nonlinear Systems,
Phase Space, Estimating the Embedding Parameters,
Quantifying Trajectories in Phase Space: The Lyapunov
Exponent, Nonlinear Analysis: The Correlation
Dimension, Tests for Nonlinearity: Su rrogate Data
Analysis
Nonlinearity Detection: Information -Based Methods
: Information and Regularity, Mutual Information
Function, Spectral Entropy, Phase -Space -Based
Entropy Methods, Detrended Fluctuation Analysis 12 CO3
IV Image Processing: Filters, Transformations, and
Registration : Two-Dimensional Fourier Transform,
Linear Filtering, Spatial Transformations, Image
Registration
Image Segmentation : Pixel -Based Methods,
Continuity -Based Methods, Multi thresholding
Morpholog ical Operations, Edge -Based Segmentation
Image Acquisition and Reconstruction : Imaging
Modalities, CT, PET, and SPECT, Magnetic Resonance
Imaging, Functional MRI
12 CO4
V Classification I: Linear Discriminant Analysis and
Support Vector Machines : Linea r Discriminators,
Evaluating Classifier Performance, Higher Dimensions:
Kernel Machines
Support Vector Machines, Machine Capacity:
Overfitting or ―Less Is More", Extending the Number
of Variables and Classes, Cluster Analysis
Classification II: Adaptive Ne ural Nets : Training the
McCullough Pitts Neuron, The Gradient Decent
Method or Delta Rule, Two -Layer Nets: Back
Projection, Three -Layer Nets, Training Strategies,
Multiple Classifications, Multiple Input Variables
12 CO5


Books and References:
Sr. No. Title Author/s Publisher Edition Year
1. Biosignal and Medical
Image Processing John L. Semmlow ,
Benjamin Griffel CRC Press 3rd 2014
2. Biomedical Signal and
Image Processing Kayvan Najarian
Robert Splinter CRC Press 2nd 2012
3. Introduction to
Biomedical Imaging Andrew Webb Wiley -
Interscience 2003

Page 29

23 M. Sc (Information Technology) Semester – III
Course Name: Biomedical Image Processing Practical Course Code: PSIT3P3b
Periods per week (1 Period is 60 minutes) 4
Credits 2
Hours Marks
Evaluation System Practical Examination 2 50
Internal -- -

List of Practical:
10 practicals covering the entire syllabus must be performed. The detailed list of
practical will be circulated later in the official workshop.


Course Outcomes:
After completion of the course, a student should be able to:
CO1: Understand basics of Bio signals and various classical techniques of bio signal
processing.
CO2: Understand various modern spectral analysis techniques.
CO3: Understand and apply various multivari ate analysis techniques on bio signals.

CO4: Understand and apply various transformations filters to images, and different
techniques for image acquisition and construction.
CO5: Understand the AI perspective in biological image processing using SVM and N eural
Networks.

Page 30

24 PSIT303c : Cloud Management
M. Sc (Information Technology) Semester – III
Course Name: Cloud Management Course Code: PSIT303c
Periods per week (1 Period is 60 minutes) 4
Credits 4
Hours Marks
Evaluation System Theory Examination 2½ 60
Internal -- 40

Course Objectives:

 To Understand the Fundamental Ideas Behind Cloud Computing, The Evolution Of
The Paradigm, Its Applicability; Benefits, As Well As Current And Future
Challenges;
 The Basic ideas And Principles In Data Center Design; Cloud Management
Techniques And Cloud Software Deployment Considerations;
 Different CPU, Memory And I/O Virtualization Techniques That Serve In Offering
Software, Computation
 And Storage Services On The Cloud; Software Defined Netwo rks (SDN) And
Software Defined Storage (SDS);
 Cloud Storage Technologies And Relevant Distributed File Systems, Nosql Databases
And Object Storage;
 The Variety Of Programming Models And Develop Working Experience In Several
Of Them.

Unit Details Lectures Outcome
I What is VMM? What's new in VMM
Get Started Release notes - VMM
Turn telemetry data on/off Deploy a VMM cloud Create
a VMM cloud Manage a VMM cloud Deploy a guarded
host fabric
Deploy guarded hosts Configure fallback HGS settings
Deploy a shielded VHDX and VM template Deploy a
shielded VM
Deploy a shielded Linux VM Deploy and manage a
software defined network (SDN) infrastructure Deploy
an SDN network controller Deploy an SDN SLB Deploy
an SDN RAS gateway Deploy SDN using PowerShell
Set up a VM network in SDN
Encrypt VM networks in SDN Allow and block VM
traffic with SDN port ACLs Control SDN virtual
network bandwidth with QoS Load balance network
traffic Set up NAT for traffic forwarding in an SDN
Route traffic across networks in the SDN in frastructure
Configure SDN guest clusters Update the NC server
certificate Set up SDN SLB VIPs Back up and restore the
SDN infrastructure
Remove an SDN from VMM Manage SDN resources in 12 CO1

Page 31

25 the VMM fabric Deploy and manage Storage Spaces
Direct Set up a hyper -converged Storage Spaces Direct
cluster Set up a disaggregated Storage Spaces Direct
cluster Manage Storage Spaces Direct clusters Assign
storage QoS policies for Clusters How To Plan System
requirements – VMM Plan VMM installation Plan a
VMM high availabi lity deployment Identify VMM ports
and protocols Plan the VMM compute fabric Plan the
VMM networking fabric Identify supported storage
arrays Upgrade and install
Upgrade VMM Install VMM Install the VMM console
Enable enhanced console session Deploy VMM for high
availability Deploy a highly available VMM
management server Deploy a highly available SQL
Server database for VMM Deploy a highly available
VMM library Set up TLS 1.2 Deploy update rollups
Back up and restore VMM Manage the VMM library
Library overv iew Add file -based resources to the VMM
library
Add profiles to the VMM library Add VM templates to
the VMM library Add service templates to the VMM
library Manage VMM library resources Manage
virtualization servers Manage VMM host groups Add
existing Hype r-V hosts and clusters to the fabric Add a
Nano server as a Hyper -V host or cluster Run a script on
host
Create a cluster from standalone Hyper -V hosts
Provision a Hyper -V host or cluster from bare -metal
Create a guest Hyper -V cluster from a service templa te
Set up networking for Hyper -V hosts and clusters Set up
storage for Hyper -V hosts and clusters Manage MPIO for
Hyper -V hosts and clusters Manage Hyper -V extended
port ACLs Manage Hyper -V clusters Update Hyper -V
hosts and clusters Run a rolling upgrade o f Hyper -V
clusters Service Hyper -V hosts for maintenance Manage
VMware servers Manage management servers Manage
infrastructure servers Manage update servers Manage
networking Network fabric overview Set up logical
networks Set up logical networks in UR1 Se t up VM
networks
Set up IP address pools Add a network gateway Set up
port profiles Set up logical switches Set up MAC address
pools Integrate NLB with service templates Set up an
IPAM server Manage storage Set up storage fabric Set up
storage classificati ons Add storage devices Allocate
storage to host groups Set up a Microsoft iSCSI Target
Server Set up a Virtual Fibre Channel Set up file storage
Set up Storage Replica in VMM

Page 32

26

II Service Manager What's new in Service Manager Get
started
Evaluation and activation of Service Manager Service
Manager components Supported configurations System
requirements - Service Manager Release notes - Service
Manager Enable service log on Manage telemetry
settings How to Plan
Planning for Service Manager Plan for deployment
Service Manager editions Recommended deployment
topologies Operations Manager considerations Service
Manager databases
Port assignments Prepare for deployment Service
Manager performance Plan for performance and
scalability Plan for har dware performance Deploy
Deploy Service Manager Deployment scenarios Install
on a single computer Install on two computers
Install on four computers Set up remote SQL Server
Reporting Services Use SQL Server AlwaysOn
availability groups for failover
Create and deploy server images Install on VMs
Configure PowerShell Register with the data warehouse
to enable reporting Deploy additional management
servers Deployment considerations with a disjointed
namespace Learn about the new Self Service portal
Deploy the Self-Service portal Set up load balancing
Back up the encryption key Index non -English
knowledge articles
Troubleshoot deployment issues Deploy from a
command line
Move databases Upgrade Upgrade Service Manager
Upgrade the self -service portal to Service M anager 2016
Upgrade SQL Server Reporting Services Set up a lab
environment for upgrade Prepare the production
environment Prepare the lab environment Run an
upgrade Complete tasks after upgrade Troubleshoot
upgrade issues
Administer Use management packs to add functionality
Use connectors to import data Import data from Active
Directory Domain Services Import data and alerts from
Operations Manager
Import data from Configuration Manager Import
runbooks from Orchestrator Import data from VMM Use
a CSV file t o import data
Optionally disable ECL logging for faster connector
synchronization Configuration items Configure incident
management Configure service level management
Configure workflows Configure change and activity
management Configure release management Configure 12 CO2

Page 33

27 Desired Configuration Management to generate incidents
Configure notifications Use the service catalog to offer
services Use groups, queues, and lists in Service
Manager
Use runbooks to automate procedures User interface
customization
Manage user roles Manage Run As accounts Manage
knowledge articles Configure and use Service Manager
cmdlets Manage the data warehouse Register source
systems to the data warehouse
Troubleshoot computer problems with tasks Configure
your preference for sharing di agnostic and usage data
Operate Search for information Manage incidents and
problems Manage changes and activities Manage service
requests Manage release records
Data warehouse reporting and analytics Use and manage
standard reports
III What is Configuration Manager? Microsoft Endpoint
Configuration Manager FAQ What happened to SCCM?
Introduction
Find help for Configuration Manager How to use the
docs
How to use the console Accessibility features Software
Center user guide Fundamentals Configurat ion Manager
fundamentals
Sites and hierarchies About upgrade, update, and install
Manage devices Client management Security Role -based
administration Configuration Manager and Windows as a
Service
Plan and design Get ready for Configuration Manager
Product changes Features and capabilities Security and
privacy for Configuration Manager Security and privacy
overview
Plan for security Security best practices and privacy
information
Privacy statement - Configuration Manager Cmdlet
Library Additional privacy in formation Configure
security Cryptographic controls technical reference
Enable TLS About enabling TLS Enable TLS on clients
Enable TLS on site servers and remote site systems
Common issues when enabling TLS 1Migrate data
between hierarchies Migration over view Plan for
migration Planning for migration Prerequisites for
migration Checklists for migration
Determine whether to migrate data Planning the source
hierarchy
Planning migration jobs Planning client migration
Planning for content deployment Planning t o migrate
objects Planning to monitor migration Planning to
complete migration Configure source hierarchies and 12 CO3

Page 34

28 source sites Operations for migrating Security and
privacy for migration Deploy servers and roles Deploy
servers and roles Install infrastructur e Get installation
media Before you run setup Setup reference Setup
downloader Prerequisite checker
Prerequisite checks Installing sites Prepare to install sites
overview
Prepare to install sites Prerequisites for installing sites
Use the setup wizard Use a command -line Command -
line overview Command -line options Install consoles
Upgrade an evaluation install
Upgrade to Configuration Manager Scenarios to
streamline your inst allation Configure sites and
hierarchies Configure sites and hierarchies overview Add
site system roles Add site system roles overview Install
site system roles Install cloud -based distribution points
About the service connection point Configuration option s
for site system roles Database replicas for management
points Site components Publish site data Manage content
and content infrastructure Content infrastructure
overview Install and configure distribution points Deploy
and manage content Monitor content
Microsoft Connected Cache Troubleshoot Microsoft
Connected Cache Run discovery Discovery methods
overview About discovery methods Select discovery
methods Configure discovery methods Site boundaries
and boundary groups Site boundaries and boundary
groups o verview Boundaries Boundary groups
Procedures for boundary groups High availability High
availability options Site server high availability
Flowchart - Passive site server setup Flowchart - Promote
site server (planned) Flowchart - Promote site server
(unplanned) Prepare to use SQL Server Always On
Configure SQL Server Always On Use a SQL Server
cluster
Custom locations for database files Configure role -based
administration
IV What's new in Orchestrator Automate with runbooks Get
started
Install Orc hestrator Work with runbooks in the
Orchestrator console
Example runbook: Creating a runbook to monitor a
folder Release notes – Orchestrator Turn on/off telemetry
How To Plan
Database sizing and performance Feature performance
considerations System requir ements – Orchestrator
Design a runbook Deploy Upgrade Orchestrator Deploy
runbooks Configure Orchestrator database connections
Migrate Orchestrator between environments Change the
Orchestrator database Manage Runbooks 12 CO4

Page 35

29 Design and build runbooks Create and t est a sample
runbook Control runbook activities Monitor activities
Runbook properties
Track runbooks Install TLS Install and enable TLS 1.2
Manage Orchestrator Servers Runbook permissions Back
up Orchestrator
Bench mark Optimize performance of .Net activit ies
Configure runbook throttling Recover a database
Recover web components
Add an integration pack View Orchestrator data with
PowerPivot Change Orchestrator user groups Common
activity properties Computer groups Standard Activities
Orchestrator standard a ctivities Alphabetical list of
Standard Activities Ports and protocols of Standard
Activities System Run Program Run .NET Script End
Process Start/Stop Service Restart System Save Event
Log Query WMI Run SSH Command Get SNMP
Variable
Monitor SNMP Trap Send SNMP Trap Set SNMP
Variable
Scheduling Monitor Date/Time Check Schedule
Monitoring
Monitor Event Log Monitor Service Get Service Status
Monitor Process Get Process Status Monitor
Computer/IP Get Computer/IP Status Monitor Disk
Space Get Disk Space Status Monitor Internet
Application Get Internet Application Status Monitor
WMI File Management Compress File Copy File Create
Folder Decompress File Delete File Delete Folder Get
File Status Monitor File Monitor Folder Move File Move
Folder PGP Decrypt File PGP Encrypt File
Print File Rename File Email Send Email Notification
Send Event Log Message Send Syslog Message Send
Platform Event Utilities Apply XSLT Query XML Map
Published Data Compare Values
Write Web Pages Read Text Log Write to Database
Query Database
Monitor Counter Get Counter Value Modify Counter
Invoke Web Services Format Date/Time Generate
Random Text Map Network Path Disconnect Network
Path Get Dial -up Status Connect/Disconnect Dial -up
Text File Management Append Line
Delete Line Find Text Get Li nes Insert Line Read Line
Search and Replace Text Runbook Control Invoke
Runbook Initialize Data Junction Return Data
Orchestrator Integration Toolkit Overview of
Orchestrator Integration Toolkit Installation Command
Line Activity Wizard Integration Pack W izard
Integration Packs Active Directory Active Directory
activities Add Computer To Group

Page 36

30 Add Group To Group Add User To Group Create
Computer
Create Group Create User Delete Computer Delete
Group Delete User Disable Computer Disable User
Enable Computer Enable User
Get Computer Get Group Get Organizational Unit Get
User Move Computer Move Group Move User Remove
Computer From Group
Remove Group From Group Remove User From Group
Rename Group Rename User Reset User Password
Unlock User Update Computer Update Group Update
User
V Data Protection Manager How does DPM work?
What can DPM back up? DPM -compatible tape libraries
Get Started DPM build versions DPM release notes
What's new in DPM What DPM supports How To
Plan Your DPM Environment Get ready to deploy DPM
servers
Prepare your environment for DPM Prepare data storage
Identify compatible tape libraries Identify data sources
you want to protect Install or Upgrade DPM Install DPM
Upgrade your DPM installation Add Modern Backup
storage
Deduplicate DPM storage Deploy DPM Deploy the DPM
protection agent Deploy protection groups Configure
firewall settings Offline backup Using own disk Protect
Workloads Back up Hyper -V virtual machines Back up
Exchange with DPM Back up SharePoint with DPM
Back up SQL Serv er with DPM Back up client
computers with DPM Back up file data with DPM Back
up system state and bare metal Back up and restore
VMware servers Back up and restore VMM servers
Prepare to back up a generic data source Prepare
machines in workgroups and untr usted domains for
backup Back up the DPM server Monitor and Manage
Monitor DPM Set up DPM logging Generate DPM
reports Use SCOM to manage and monitor DPM servers
Improve replication performance Use central console to
manage DPM servers 12 CO5

Books and R eferences:
Sr. No. Title Author/s Publisher Edition Year
1. Microsoft SCVMM 2019 Whitepaper Microsoft 2019
2. Microsoft Endpoint
Manager 2019 Whitepaper Microsoft 2019
3. Microsoft SCO 2019 Whitepaper Microsoft 2019
4. Microsoft SCOM 2019 Whitepaper Microsoft 2019
5. Microsoft SCSM 2019 Whitepaper Microsoft 2019
6. Microsoft DPM 2019 Whitepaper Microsoft 2019
7. Introducing Microsoft Mitch Tulloch with Microsoft 2012

Page 37

31 System Center 2012 Symon Perriman and
the System Center
Team Press



M. Sc (Information Technology) Semester – III
Course Name: Cloud Management Practical Course Code: PSIT3P3c
Periods per week (1 Period is 60 minutes) 4
Credits 2
Hours Marks
Evaluation System Practical Examination 2 50
Internal -- -


List of Practical:
10 practicals covering the entire syllabus must be performed. The detailed list of
practical will be circulated later in the official workshop.


Course Outcomes:
After completion of the course, a student should be able to:

CO1: Under stand the concepts of VMM, SDN, NAS , HyperV etc.
CO2: Understand and demonstrate the use of Service manager with various deployments that
can be performed using it.
CO3: Understand SCCM and Demonstrate the use of Configuration Manager
CO4: Understand automation with runbooks and demonstrate the use of Windows
Orchestrator
CO5: Understand and demonstrate the use of Data Protection Manager

Page 38

32





PSIT303d : Malware Analysis
M. Sc (Information Technology) Semester – III
Course Name: Malware Analysis Course Code: PSIT303d
Periods per week (1 Period is 60 minutes) 4
Credits 4
Hours Marks
Evaluation System Theory Examination 2½ 60
Internal -- 40

Course Objectives:
 Possess the skills necessary to carry out independent analysis of modern malware
samples using both static and dynamic analysis techniques.
 Have an intimate understanding of executable formats, Windows internals and API,
and analysis techniques.
 Extract investigative leads from host and network -based indicators associated with a
malicious program.
 Apply techniques and concepts to unpack, extract, decrypt, or bypass new
anti­analysis techniques in future malware samples.
 Achieve proficiency with industry standard tools including IDA Pro, OllyDbg,
WinDBG, PE Explorer, ProcMon etc.

Unit Details Lectures Outcome
I Malware Analysis: Introduction, Techniques, Types of
malware, General rules for Malware Analysis. Basic
Static Techniques: Antivirus Scanning, Hashing,
Finding Strings, Packed and Obfuscated Malware,
Portable Executable Malware, Portable executable File
Format, Linked Libraries and Functions, Static Analysis,
The PE file headers and sections. Malware Analysis in
Virtual Machines: Structure of VM, Creating and using
Malware Analysis machine, Risks of using VMware for
malware analysis, Record/Replay. Basic Dynamic
Analysis: Sandboxes, Running Malware, Monitoring
with process monitor, Viewing processes with process
explorer, Comparing registry snapsh ots with regshot,
Faking a network, Packet sniffing with Wireshark, Using
INetSim, Basic Dynamic Tools. x86 Disassembly 12 CO1
II IDA PRO: Loading an executable, IDA Pro Interface,
Using cross references, Analysing functions, Using
graphing options, Enhan cing disassembly, Extending
IDA with plug -ins.
Recognising C Code constructs in assembly: Global 12 CO2

Page 39

33 v/s local variables, Disassembling arithmetic operations,
recognizing if statements, recognizing loops, function
call conventions, Analysing switch statements,
Disassembling arrays, Identifying structs, Analysing
linked list traversal. Analysing Malicious Windows
Programs: The windows API, The Windows Registry,
Networking APIs, Understanding running malware.
Kernel v/s user mode, Native API.
Advanced Dynamic An alysis – Debugging: Source -
level v/s Assembly -level debugging, kernel v/s user
mode debugging, Using a debugger, Exceptions,
Modifying execution with a debugger, modifying
program execution.
III Advanced Dynamic Analysis – OLLYDBG: Loading
Malware, The Ollydbg Interface, Memory Map, Viewing
threads and Stacks, Executing code, Breakpoints,
Loading DLLs, Tracing, Exception handling, Patching,
Analysing shell code, Assistance features, Plug -ins,
Scriptable debugging. Kernel Debugging wi th
WINDBG: Drivers and kernel code, Using WinDbg,
Microsoft Symbols, kernel debugging and using it,
Rootkits, Loading drivers, kernel issues with windows.
Malware Functionality – Malware Behavior:
Downloaders and launchers, Backdoors, Credential
stealers, Persistence mechanisms, Privilege escalation,
covering the tracks.
Covert Malware Launching: Launchers, Process
injection, Process replacement, Hook injection, detours,
APC injection. 12 CO3
IV Data Encoding: Goal of Analysing algorithms, Simple
ciphers, Common cryptographic algorithms, Custom
encoding, decoding.
Malware – focused network signatures: Network
countermeasures , Safely investigating attacker online,
Content -Based Network Countermeasures, Combining
Dynamic and Stat ic Analysis Techniques, Understanding
the Attacker’s Perspective .
Anti -disassembly: Concepts, Defeating disassembly
algorithms, anti -disassembly techniques, Obscuring flow
control, Thwarting stack -frame analysis.
Anti -debugging: Windows debugger detection ,
debugger behavior, Interfering with debugger
functionality, Debugger vulnerabilities. 12 CO4
V Anti -virtual machine techniques: VMWare artifacts,
Vulnerable functions, Tweaking settings, Escaping the
virtual machine.
Packers and unpacking: Packer anatomy, Identifying
Packed Programs, Unpacking options, Automated
Unpacking, Manual Unpacking, Common packers,
Analysing without unpacking, Packed DLLs, 12 CO5

Page 40

34 Shellcode Analysis: Loading shellcode for analysis,
Position -independent Code, Identifying Exe cution
Location, Manual Symbol Resolution, Shellcode
encoding, NOP Sleds, Finding Shellcode.
C++ Analysis: OOP, Virtual and Non -virtual functions,
Creating and destroying objects.
64-bit Malware: Why 64 -bit malware? Differences in
x64 architecture, Windows 32-bit on Windows 64 -bit,
64-bit hints at malware functionality.

Books and References:
Sr. No. Title Author/s Publisher Edition Year
1. Practical Malware
Analysis – The Hands -On
Guide to Dissecting
Malicious Software Michael Sikorski,
Andrew Honig No
Scratch
Press - 2013
2. Mastering Malware
Analysis
Alexey Kleymenov,
Amr Thabet Packt
Publishing - 2019
3. Windows Malware
Analysis Essentials Victor Marak Packt
Publishing 2015

M. Sc (Information Technology) Semester – III
Course Name: Malware Analysis Practical Course Code: PSIT3P3d
Periods per week (1 Period is 60 minutes) 4
Credits 2
Hours Marks
Evaluation System Practical Examination 2 50
Internal -- -

List of Practical:
10 practicals covering the entire syllabus must be performed. The detailed list of
practical will be circulated later in the official workshop.

Course Outcomes:
After completion of the course, a student should be able to:
CO1: Understand various introductory techniqu es of malware analysis and creating the
testing environment
CO2: Perform advanced dynamic analysis and recognize constructs in assembly code.
CO3: Perform Reverse Engineering using OLLYDBG and WINDBG and study the
behaviours and functions of malware
CO4: Understand data encoding, various techniques for anti -disassembly and anti -debugging
CO5: Understand various anti virtual machine techniques and perform shellcode analysis of
various languages along with x64 architecture.

Page 41

35





PSIT304a : Robotic Process Automation
M. Sc (Information Technology) Semester – III
Course Name: Robotic Process Automation Course Code: PSIT304a
Periods per week (1 Period is 60 minutes) 4
Credits 4
Hours Marks
Evaluation System Theory Examination 2½ 60
Internal -- 40

Course Objectives:

 To make the students aware about the automation today in the industry.
 To make the students aware about the tools used for automation.
 To help the students automate a complete process

Unit Details Lectures Outcome
I Robotic Process Automation: Scope and techniques of
automation, About UiPath
Record and Play: UiPath stack, Downloading and
installing UiPath Studio, Learning UiPath Studio, Task
recorder, Step -by-step examples using the recorder. 12 CO1
II Sequence, Flowchart, and Control Flow: Sequencing
the workflow, Activities, Control flow, various types of
loops, and decision making, Step -by-step example
using Sequence and Flowchart, Step -by-step example
using Sequence and Control flow
Data Manipulation: Variables and scope , Collections,
Arguments – Purpose and use, Data table usage with
examples, Clipboard management, File operation with
step-by-step example, CSV/Excel to data table and vice
versa (with a step -by-step example)
12 CO2
III Taking Control of the Controls : Finding and
attaching windows, Finding the control, Techniques for
waiting for a control, Act on controls – mouse and
keyboard activities, Working with UiExplorer,
Handling events, Revisit recorder, Screen Scraping,
When to use OCR, Types of OCR available, How to
use OCR, Avoiding typical failure points
Tame that Application with Plugins and Extensions:
Terminal plugin, SAP automation, Java plugin, Citrix
automation, Mail plugin, PDF plugin, Web integration, 12 CO3

Page 42

36 Excel and Word plugins, Credential management,
Extensions – Java, Chrome, Firefox, and Silverlight
IV Handling User Events and Assistant Bots: What are
assistant bots?, Monitoring system event triggers,
Hotkey trigger, Mouse trigger, System trigger
,Monitoring image and element triggers, An examp le of
monitoring email, Example of monitoring a copying
event and blocking it, Launching an assistant bot on a
keyboard event
Exception Handling, Debugging, and Logging:
Exception handling, Common exceptions and ways to
handle them, Logging and taking scre enshots,
Debugging techniques, Collecting crash dumps, Error
reporting 12 CO4
V Managing and Maintaining the Code: Project
organization, Nesting workflows, Reusability of
workflows, Commenting techniques, State Machine,
When to use Flowcharts, State Mach ines, or Sequences,
Using config files and examples of a config file,
Integrating a TFS server
Deploying and Maintaining the Bot: Publishing using
publish utility, Overview of Orchestration Server,
Using Orchestration Server to control bots, Using
Orchest ration Server to deploy bots, License
management, Publishing and managing updates 12 CO5

Books and References:
Sr. No. Title Author/s Publisher Edition Year
1. Learning Robotic Process
Automation Alok Mani
Tripathi Packt 1st 2018
2. Robotic Process
Automation Tools, Process
Automation and their
benefits: Understanding
RPA and Intelligent
Automation Srikanth Merianda Createspace
Independent
Publishing 1st 2018
3. The Simple
Implementation Guide to
Robotic Process
Automation (Rpa): How to
Best Implem ent Rpa in an
Organization Kelly
Wibbenmeyer iUniverse
1st 2018

M. Sc (Information Technology) Semester – III
Course Name: Robotic Process Automation Course Code: PSIT3P4a
Periods per week (1 Period is 60 minutes) 4
Credits 2
Hours Marks
Evaluation System Practical Examination 2 50

Page 43

37 Internal -- -

List of Practical:
10 practicals covering the entire syllabus must be performed. The detailed list of
practical will be circulated later in the official workshop.

Course Outcomes:

After completing the course, a learner will be able to:

CO1: Understand the mechanism of business process and can provide the solution in an
optimize way.

CO2: Understand the features use for interacting with database plugins.

CO3: Use the plug -ins and other controls used for process automation.

CO4: Use and handle the different events, debugging and managing the errors.

CO5: Test and deploy the automated process.

Page 44

38





PSIT304b : Virtual Reality and Augmented Reality
M. Sc (Information Technology) Semester – III
Course Name: Virtual Reality and Augmented Reality Course Code: PSIT304b
Periods per week (1 Period is 60 minutes) 4
Credits 4
Hours Marks
Evaluation System Theory Examination 2½ 60
Internal -- 40

Course Objectives:

 To learn background of VR including a brief history of VR, different forms of VR and
related technologies, and broad overview of some of the most important concepts
 To provide background in perception to educate VR creators on concepts and the ories
of how we perceive and interact with the world around us
 To make learner aware of high -level concepts for designing/building assets and how
subtle design choices can influence user behavior
 To learn about art for VR and AR should be optimized for spa tial displays with
spatially aware input devices to interact with digital objects in true 3D
 Walkthrough of VRTK, an open source project meant to spur on cross -platform
development

Unit Details Lectures Outcome
I Introduction: What Is Virtual Reality, A History of VR,
An Overview of Various Realities, Immersion,
Presence, and Reality Trade -Offs, The Basics: Design
Guidelines, Objective and Subjective Reality,
Perceptual Models and Processes, Perceptual
Modalities 12 CO1
II Perception of Space and Time, P erceptual Stability,
Attention, and Action, Perception: Design Guidelines,
Adverse Health Effects, Motion Sickness, Eye Strain,
Seizures, and Aftereffects, Hardware Challenges,
Latency, Measuring Sickness, Reducing Adverse
Effects, Adverse Health Effects: Design Guidelines 12 CO2
III Content Creation, Concepts of Content Creation,
Environmental Design, Affecting Behavior,
Transitioning to VR Content Creation, Content
Creation: Design Guidelines, Interaction, Human -
Centered Interaction, VR Interaction Concepts, Input
Devices, Interaction Patterns and Techniques,
Interaction: Design Guidelines 12 CO3

Page 45

39 IV Design and Art Across Digital Realities, Designing for
Our Senses, Virtual Reality for Art, 3D Art
Optimization, Computer Vision That Makes
Augmented Re ality Possible Works, Virtual Reality and
Augmented Reality: Cross -Platform Theory 12 CO4
V Virtual Reality Toolkit: Open Source Framework for
the Community, Data and Machine Learning
Visualization Design and Development in Spatial
Computing, Character AI and Behaviors, The Virtual
and Augmented Reality Health Technology Ecosystem 12 CO5

Books and References:
Sr. No. Title Author/s Publisher Edition Year
1. The VR Book, Human
Centered Design for
Virtual Reality Jason Jerald ACM
Books 1st 2016
2. Creating Augmented and
Virtual Realities Erin Pangilinan,
Steve Lukas,
Vasanth Mohan O’Reilly 1st 2019
3. Virtual reality with
VRTK4 Rakesh Baruah APress 1st 2020

M. Sc (Information Technology) Semester – III
Course Name: Virtual Reality and Augmented Reality
Practical Course Code: PSIT3P4b
Periods per week (1 Period is 60 minutes) 4
Credits 2
Hours Marks
Evaluation System Practical Examination 2 50
Internal -- -


List of Practical:
10 practicals covering the entire syllabus must be performed. The detailed list of
practical will be circulated later in the official workshop.


Course Outcomes:

After completion of the course, a student should be able to:

CO1: Apply the concepts of VR and AR in real life.
CO2: Reduce the greatest risk to VR.
CO3: Design the way users interact within the scenes they find themselves in.
CO4: be exposed to VR, AR and today’s resources
CO5: Effectively use open source VR software.

Page 46

40






PSIT304c : Data Centre Technologies
M. Sc (Information Technology) Semester – III
Course Name: Data Centre Technologies Course Code: PSIT304c
Periods per week (1 Period is 60 minutes) 4
Credits 4
Hours Marks
Evaluation System Theory Examination 2½ 60
Internal -- 40

Course Objectives:

 Identify important requirements to design and support a data center.
 Determine a data center environment’s requirement including systems and network
architecture as well as services.
 Evaluate options for server farms, network designs, h igh availability, load balancing,
data center services, and trends that might affect data center designs.
 Assess threats, vulnerabilities and common attacks, and network security devices
available to protect data centers.
 Design a data center infrastructur e integrating features that address security,
performance, and availability.
 Measure data center traffic patterns and performance metrics.

Unit Details Lectures Outcome
I Virtualization History and Definitions
Data Center Essential Definitions
Data Center Evolution Operational Areas and Data
Center Architecture The Origins of Data Center
Virtualization Virtual Memory
Mainframe Virtualization Hot Standby Router Protocol
Defining Virtualization
Data Center Virtualization Timeline
Classifying Virtualiza tion Technologies
A Virtualization Taxonomy Virtualization Scalability
Technology Areas Classification Examples Summary
Data Center Network Evolution
Ethernet Protocol: Then and Now
Ethernet Media Coaxial Cable
Twisted -Pair Optical Fiber Direct -Attach Twin axial
Cables Ethernet Data Rate Timeline Data Center
Network Topologies
Data Center Network Layers Design Factors for Data 12 CO1

Page 47

41 Center Networks Physical Network Layout
Considerations The ANSI/TIA -942 Standard Network
Virtualization Benefits
Network Logical Part itioning Network Simplification
and Traffic Load Balancing
Management Consolidation and Cabling Optimization
Network Extension
The Humble Beginnings of Network Virtualization
Network Partitioning
Concepts from the Bridging World
Defining VLANs VLAN Trunks
Two Common Misconceptions About VLANs
Misconception Number 1: A VLAN Must Be Associated
to an IP Subnet
Misconception Number 2: Layer 3 VLANs
Spanning Tree Protocol and VLANs Spanning Tree
Protocol at Work Port States
Spanning Tree Protocol Enhancements
Spanning Tree Instances Private VLANs
VLAN Specifics Native VLAN
Reserved VLANs IDs Resource Sharing
Control and Management Plane
Concepts from the Routing World
Overlapping Addresses in a Data Center
Defining and Configuring VRFs
VRFs and Routing Protocols
VRFs and the Management Plane
VRF -Awareness VRF Resource Allocation Control
II An Army of One: ACE Virtual Contexts
Application Networking Services The Use of Load
Balancers Load -Balancing Concepts Layer 4 Switching
Versus Layer 7 Switching Connection Management
Address Translation and Load Balancing Server NAT
Dual NAT Port Redirection Transparent Mode Other
Load -Balancing Applications Firewall Load Balancing
Reverse Proxy Load Balancing Offloading Servers SSL
Offload TCP Offload HTTP Compre ssion Load Balancer
Proliferation in the Data Center Load Balancer
Performance Security Policies Suboptimal Traffic
Application Environment Independency ACE Virtual
Contexts
Application Control Engine Physical Connections
Connecting an ACE Appliance Connec ting an ACE
Module Creating and Allocating Resources to Virtual
Contexts
Integrating ACE Virtual Contexts to the Data Center
Network Routed Design Bridged Design One -Armed
Design Managing and Configuring ACE Virtual Contexts
Allowing Management Traffic to a Virtual Context
Allowing Load Balancing Traffic Through a Virtual 12 CO2

Page 48

42 Context Controlling Management Access to Virtual
Contexts
ACE Virtual Context Additional Characteristics Sharing
VLANs Among Contexts Virtual Context Fault
Tolerance
Instant Switches: Vir tual Device Contexts
Extending Device Virtualization Why Use VDCs? VDCs
in Detail Creating and Configuring VDCs VDC Names
and CLI Prompts Virtualization Nesting Allocating
Resources to VDCs Using Resource Templates
Managing VDCs VDC Operations
Processes Fa ilures and VDCs VDC Out -of-Band
Management Role -Based Access Control and VDCs
Global Resources
Fooling Spanning Tree
Spanning Tree Protocol and Link Utilization
Link Aggregation Server Connectivity and NIC Teaming
Cross -Switch PortChannels
Virtual PortChan nels Virtual PortChannel Definitions
Configuring Virtual PortChannels
Step 1: Defining the Domain
Step 2: Establishing Peer Keepalive Connectivity
Step 3: Creating the Peer Link
Step 4: Creating the Virtual PortChannel
Spanning Tree Protocol and Virtual Port Channels Peer
Link Failure and Orphan Ports
First-Hop Routing Protocols and Virtual Port Channels
Layer 2 Multipathing and vPC+
FabricPath Data Plane FabricPath Control Plane
FabricPath and Spanning Tree Protocol
Virtual PortChannel Plus
Virtualized Chassis with Fabric Extenders
Server Access Models Understanding Fabric Extenders
Fabric Extender Options
Connecting a Fabric Extender to a Parent Switch Fabric
Extended Interfaces and Spanning Tree Protocol Fabric
Interfaces Redundancy Fabric Extender Top ologies
Straight -Through Topologies Dual -Homed Topologies
III Virtualized Chassis with Fabric Extenders
Server Access Models Understanding Fabric Extenders
Fabric Extender Options
Connecting a Fabric Extender to a Parent Switch Fabric
Extended Int erfaces and Spanning Tree Protocol Fabric
Interfaces Redundancy Fabric Extender Topologies
Straight -Through Topologies Dual -Homed Topologies
Use Case: Mixed Access Data Center
A Tale of Two Data Centers
A Brief History of Distributed Data Centers
The Cold Age (Mid -1970s to 1980s) The Hot Age (1990s
to Mid -2000s) The Active -Active Age (Mid -2000s to 12 CO3

Page 49

43 Today) The Case for Layer 2 Extensions Challenges of
Layer 2 Extensions Ethernet Extensions over Optical
Connections Virtual PortChannels
FabricPath Ethe rnet Extensions over MPLS
MPLS Basic Concepts Ethernet over MPLS
Virtual Private LAN Service Ethernet Extensions over IP
MPLS over GRE
Overlay Transport Virtualization OTV Terminology
OTV Basic Configuration
OTV Loop Avoidance and Multihoming
Migration to OTV OTV Site Designs
VLAN Identifiers and Layer 2 Extensions
Internal Routing in Connected Data Centers
Use Case: Active -Active Greenfield Data Centers
Summary
Storage Evolution
Data Center Storage Devices
Hard Disk Drives Disk Arrays
Tape Drives and Libra ries Accessing Data in Rest Block -
Based Access Small Computer Systems Interface
Mainframe Storage Access
Advanced Technology Attachment
File Access Network File System
Common Internet File System Record Access
Storage Virtualization Virtualizing Storage De vices
Virtualizing LUNs Virtualizing File Systems Virtualizing
SANs
IV Server Evolution
Server Architectures Mainframes RISC Servers x86
Servers x86 Hardware Evolution
CPU Evolution Memory Evolution Expansion Bus
Evolution Physical Format Evolution
Introducing x86 Server Virtualization
Virtualization Unleashed Unified Computing
Changing Personalities
Server Provisioning Challenges
Server Domain Operations Infrastructure Domain
Operations Unified Computing and Service Profiles
Building Servi ce Profiles Identifying a Service Profile
Storage Definitions Network Definitions
Virtual Interface Placement Server Boot Order
Maintenance Policy Server Assignment Operational
Policies
Configuration External IPMI Management Configuration
Management IP Add ress
Additional Policies Associating a Service Profile to a
Server Installing an Operating System Verifying
Stateless Computing
Using Policies BIOS Setting Policies
Firmware Policies Industrializing Server Provisioning 12 CO4

Page 50

44 Cloning Pools
Service Profile Templates Server Pools
Use Case: Seasonal Workloads
V Moving Targets
Virtual Network Services Definitions
Virtual Network Services Data Path
vPath -Enabled Virtual Network Services
Cisco Virtual Security Gateway: Compute Virtual
Firewall Installing Virtual Security Gateway Creating
Security Policies , Sending Data Traffic to VSG
Virtual Machine Attributes and Virtual Zones
Application Acceleration , WAN Acceleration and Online
Migration
Routing in the Virtual World
Site Selection and Server Virtualizat ion
Route Health Injection
Global Server Load Balancing
Location/ID Separation Protocol
Use Case: Virtual Data Center
The Virtual Data Center and Cloud Computing
The Virtual Data Center Automation and Standardization
What Is Cloud Computing? Cloud Implemen tation
Example Journey to the Cloud
Networking in the Clouds Software -Defined Networks
Open Stack Network Overlays 12 CO5

Books and References:
Sr. No. Title Author/s Publisher Edition Year
1. Data Center Virtualization
Fundamentals Gustavo Alessandro
Andrade Santana Cisco
Press 1st 2014

M. Sc (Information Technology) Semester – III
Course Name: Data Centre Technologies Practical Course Code: PSIT3P4c
Periods per week (1 Period is 60 minutes) 4
Credits 2
Hours Marks
Evaluation System Practical Examination 2 50
Internal -- -

List of Practical:
10 practicals covering the entire syllabus must be performed. The detailed list of
practical will be circulated later in the official workshop.

Course Outcomes:

After completion of the course, a student should be able to:

CO1: Understand basic concepts in Virtualization.
CO2: Understand concepts of Load Balancing and Aggregation /virtual switching

Page 51

45 CO3: Understand Data center Migration and Fabric Building
CO4: Understand various Changes in Server Architecture
CO5: Understand the concepts of Cloud computing and how to move towards a cloud
computing technology.


PSIT304d : Offensive Security
M. Sc (Information Technology) Semester – III
Course Name: Offensive Security Course Code: PSIT304d
Periods per week (1 Period is 60 minutes) 4
Credits 4
Hours Marks
Evaluation System Theory Examination 2½ 60
Internal -- 40

Course Objectives:

 Understanding of security requirements within an organization
 How to inspect, protect assets from technical and managerial perspectives
 To Learn various offensive strategies to penetrate the organizations security.
 To learn various tools that aid in offensive security testing.

Unit Details Lectures Outcome
I Fault Tolerance and Resilience in Cloud Computing
Environments, Securing Web Applications, Services,
and Servers, Wireless Network Security, Wireless
Sensor Network Security: The Internet of Things,
Security for the Internet of Things, Cellular Network
Security 12 CO1
II Social Engineering Deceptions and Defenses, What Is
Vulnerability Assessment, Risk Management, Insider
Threat, Disaster Recovery, Security Policies and Plans
Development 12 CO2
III Introduction to Metasploit and Supporting Tools
The importance of penetration testing
Vulnerability assess ment versus penetration testing
The need for a penetration testing framework
Introduction to Metasploit
When to use Metasploit?
Making Metasploit effective and powerful using
supplementary tools
Nessus NMAP w3af Armitage
Setting up Your Environment
Using the Kali Linux virtual machine - the easiest way
Installing Metasploit on Windows Installing Metasploit
on Linux Setting up exploitable targets in a virtual 12 CO3

Page 52

46 environment
Metasploit Components and Environment
Configuration
Anatomy and structure of Me tasploit
Metasploit components
Auxiliaries Exploits Encoders Payloads
Post, Playing around with msfconsole
Variables in Metasploit
Updating the Metasploit Framework 55
IV Information Gathering with Metasploit
Information gathering and enumeration
Transmission Control Protocol User Datagram
Protocol File Transfer Protocol
Server Message Block Hypertext Transfer Protocol
Simple Mail Transfer Protocol
Secure Shell Domain Name System
Remote Desktop Protocol
Password sniffing
Advanced search with shodan
Vulnerability Hunting with Metasploit Managing the
database
Work spaces Importing scans
Backing up the database NMAP
NMAP scanning approach Nessus
Scanning using Nessus from msfconsole
Vulnerability detection with Metasploit auxiliaries
Auto exploitation with db_autopwn
Post exploitation What is meterpreter?
Searching for content Screen capture
Keystroke logging Dumping the hashes and cracking
with JTR Shell command
Privilege esca lation
Client -side Attacks with Metasploit
Need of client -side attacks
What are client -side attacks?
What is a Shellcode? What is a reverse shell? What is a
bind shell? What is an encoder? The msfvenom utility
Generating a payload with msfvenom
Social Engineering with Metasploit
Generating malicious PDF
Creating infectious media drives 12 CO4
V Approaching a Penetration Test Using Metasploit
Organizing a penetration test
Preinteractions
Intelligence gathering/reconnaissance phase Predicting
the test grounds
Modeling threats Vulnerability analysis
Exploitation and post -exploitation
Reporting Mounting the environment
Setting up Kali Linux in virtual environment 12 CO5

Page 53

47 The fundamentals of Me tasploit
Conducting a penetration test with Metasploit
Recalling the basics of Metasploit
Benefits of penetration testing using Metasploit Open
source
Support for testing large networks and easy naming
conventions
Smart payload generation and switchin g mechanism
Cleaner exits The GUI environment
Penetration testing an unknown network Assumptions
Gathering intelligence Using databases in Metasploit
Modeling threats
Vulnerability analysis of VSFTPD backdoor The
attack procedure
The procedure of explo iting the vulnerability
Exploitation and post exploitation
Vulnerability analysis of PHP -CGI query string
parameter vulnerability
Exploitation and post exploitation
Vulnerability analysis of HFS
Exploitation and post exploitation
Maintaining access
Clearing tracks
Revising the approach
Reinventing Metasploit Ruby – the heart of Metasploit
Creating your first Ruby program
Interacting with the Ruby shell
Defining methods in the shell
Variables and data types in Ruby
Working with strings Concate nating strings The
substring function The split function Numbers and
conversions in Ruby Conversions in Ruby Ranges in
Ruby Arrays in Ruby Methods in Ruby
Decision -making operators Loops in Ruby
Regular expressions Wrapping up with Ruby basics
Develop ing custom modules Building a module in a
nutshell
The architecture of the Metasploit framework
Understanding the file structure The libraries layout
Understanding the existing modules
The format of a Metasploit module
Disassembling existing HTTP serve r scanner module
Libraries and the function
Writing out a custom FTP scanner module
Libraries and the function Using msftidy
Writing out a custom SSH authentication brute forcer
Rephrasing the equation
Writing a drive disabler post exploitation module
Writing a credential harvester post exploitation module
Breakthrough meterpreter scripting

Page 54

48 Essentials of meterpreter scripting
Pivoting the target network Setting up persistent access
API calls and mixins
Fabricating custom meterpreter scripts
Working with RailGun
Interactive Ruby shell basics
Understanding RailGun and its scripting
Manipulating Windows API calls
Fabricating sophisticated RailGun scripts
The Exploit Formulation Process
The absolute basics of exploitation
The basics The architecture System organization basics
Registers
Exploiting stack -based buffer overflows with
Metasploit
Crashing the vulnerable application
Building the exploit base Calculating the offset Using
the pattern_create tool
Using the patter n_offset tool Finding the JMP ESP
address Using Immunity Debugger to find executable
modules
Using msfbinscan Stuffing the space
Relevance of NOPs Determining bad characters
Determining space limitations
Writing the Metasploit exploit module
Exploiting SEH -based buffer overflows with Metasploit
Building the exploit base Calculating the offset Using
pattern_create tool Using pattern_offset tool Table of
Contents
Finding the POP/POP/RET address
The Mona script Using msfbinscan
Writing the Metasploit SE H exploit module Using
NASM shell for writing assembly instructions
Bypassing DEP in Metasploit modules Using msfrop
to find ROP gadgets Using Mona to create ROP chains
Writing the Metasploit exploit module for DEP bypass

Books and References:
Sr. No. Title Author/s Publisher Edition Year
1. Computer and Information
Security Handbook John R. Vacca Morgan
Kaufmann
Publisher 3rd 2017
2. Metasploit Revealed: Secrets
of the Expert Pentester Sagar Rahalkar Packt
Publishing 2017

M. Sc (Information Technology) Semester – III
Course Name: Offensive Security Practical Course Code: PSIT3P4d
Periods per week (1 Period is 60 minutes) 4
Credits 2

Page 55

49 Hours Marks
Evaluation System Practical Examination 2 50
Internal -- -

List of Practical:
10 practicals covering the entire syllabus must be performed. The detailed list of
practical will be circulated later in the official workshop.



Course Outcomes:

After completion of the course, a student should be able to:
CO1: Understand basic security issues in cloud, IoT etc.
CO2: Understand different security techniques and policies
CO3: Use Vulnerability assessment and exploitation tool
CO4: Analyze the network perform reconnaissance and enumerate the target to detect
vulnerabilities
CO5: Perform offensive tests using Metasploit on various application, generating payloads
etc.

Page 56

50































SEMESTER IV

Page 57

51










PSIT401: Blockchain
M. Sc ( Information Technology ) Semester – IV
Course Name: Blockchain Course Code: PSIT401
Periods per week (1 Period is 6 0 minutes ) 4
Credits 4
Hours Marks
Evaluation System Theory Examination 2½ 60
Internal -- 40

Course Objectives:

 To provide conceptual understanding of the function of Blockchain as a method of
securing distributed ledgers, how consensus on their contents is achieved, and the new
applications that they enable.
 To cover the technological underpinnings of blockchain operations as distributed data
structures and decision -making systems, their functionality and different architecture
types.
 To provide a critical evaluation of existing ―smart contract‖ capabilities and
platforms, and examine their future directions, opportunities, risks and challenges.

Unit Details Lectures Outcome
I Blockchain: Introduction, History, Centralised versus
Decentralised systems, Layers of blockchain,
Importance of blockchain, Blockchain uses and use
cases.
Working of Blockchain: Blockchain foundation,
Cryptography, Game Theory, Computer Science
Engineering, Properties of blockchain solutions,
blockchain transactions, distributed consensus
mechanisms, Blockchain mechanisms, Scaling
blockchain
Working of Bitcoin: Money, Bitcoin, B itcoin
blockchain, bitcoin network, bitcoin scripts, Full Nodes
and SVPs, Bitcoin wallets. 12 CO1
II Ethereum: three parts of blockchain, Ether as currency
and commodity, Building trustless systems, Smart
contracts, Ethereum Virtual Machine, The Mist 12 CO2

Page 58

52 browser, Wallets as a Computing Metaphor, The Bank
Teller Metaphor, Breaking with Banking History, How
Encryption Leads to Trust, System Requirements,
Using Parity with Geth, Anonymity in Crypto currency,
Central Bank Network, Virtual Machines, EVM
Applications, State Machines, Guts of the EVM,
Blocks, Mining’s Place in the State Transition
Function, Renting Time on the EVM, Gas, Working
with Gas, Accounts, Transactions, and Messages,
Transactions and Messages, Estimating Gas Fees for
Operations, Opcodes in the EVM.
Solidity Programming: Introduction, Global Banking
Made Real, Complementary Currency, Programming
the EVM, Design Rationale, Importance of Formal
Proofs, Automated Proofs, Testing, For matting Solidity
Files, Reading Code, Statements and Expressions in
Solidity, Value Types, Global Special Variables, Units,
and Functions,
III Hyperledger: Overview, Fabric, composer, installing
hyperledger fabric and composer, deploying, running
the network, error troubleshooting.
Smart Contracts and Tokens: EVM as Back End,
Assets Backed by Anything, Cryptocurrency Is a
Measure of Time, Function of Collectibles in Human
Systems, Platforms for High -Value Digital Collectibles,
Tokens as Category of Smart Contract, Creating a
Token, Deploying the Contract, Playing with Contracts. 12 CO3
IV Mining Ether: Why? Ether’s Source, Defining Mining,
Difficulty, Self -Regulation, and the Race for Profit,
How Proof of Work Helps Regulate Block Time, DAG
and Nonce, Faster Blocks, Stale Blocks, Difficulties,
Ancestry of Blocks and Transactions, Ethereum and
Bitcoin, Fo rking, Mining, Geth on Windows, Executing
Commands in the EVM via the Geth Console,
Launching Geth with Flags, Mining on the Testnet,
GPU Mining Rigs, Mining on a Pool with Multiple
GPUs.
Cryptoecnomics: Introduction, Usefulness of
cryptoeconomics, Speed o f blocks, Ether Issuance
scheme, Common Attack Scenarios. 12 CO4
V Blockchain Application Development: Decentralized
Applications, Blockchain Application Development,
Interacting with the Bitcoin Blockchain, Interacting
Programmatically with Ethereum —Sending
Transactions, Creating a Smart Contract, Executing
Smart Contract Functions, Public vs. Private
Bloc kchains, Decentralized Application Architecture,
Building an Ethereum DApp: The DApp, Setting Up
a Private Ethereum Network, Creating the Smart
Contract, Deploying the Smart Contract, Client 12 CO5

Page 59

53 Application, DApp deployment: Seven Ways to Think
About Smart Con tracts, Dapp Contract Data Models,
EVM back -end and front -end communication, JSON -
RPC, Web 3, JavaScript API, Using Meteor with the
EVM, Executing Contracts in the Console,
Recommendations for Prototyping, Third -Party
Deployment Libraries, Creating Private Chains.





Books and References:
Sr. No. Title Author/s Publisher Edition Year
1. Beginning Blockchain
A Beginner’s Guide to
Building Blockchain
Solutions Bikramaditya
Singhal,
Gautam Dhameja,
Priyansu Sekhar
Panda Apress 2018
2. Introducing Ethereum and
Solidity Chris Dannen Apress 2017
3. The Blockchain
Developer Elad Elrom Apress 2019
4. Mastering Ethereum Andreas M.
Antonopoulos
Dr. Gavin Wood O’Reilly First 2018
5. Blockchain Enabled
Applications Vikram Dhillon
David Metcalf
Max Hooper Apress 2017

M. Sc ( Information Technology ) Semester – III
Course Name: Blockchain Course Code: PSIT
Periods per week (1 Period is 6 0 minutes ) 4
Credits 2
Hours Marks
Evaluation System Practical Examination 2 50
Internal -- -

List of Practical:
10 practicals covering the entire syllabus must be performed. The detailed list of
practical will be circulated later in the official workshop.


Course Outcome s:
After completion of the course, a student should be able to:

CO1: The students would understand the structure of a blockchain and why/when it is better
than a simple distributed database.

Page 60

54 CO2: Analyze the incentive structure in a blockchain based system and critically assess its
functions, benefits and vulnerabilities

CO3: Evaluate the setting where a blockchain based structure may be applied, its potential
and its limitations

CO4: Understand what constitutes a ―smart‖ contract, what are its legal implications and
what it can and cannot do, now and in the near future

CO5: Develop blockchain DApps.

PSIT402a: Natural Language Processing
M. Sc (Information Technology) Semester – IV
Course Name: Natural Language Processing Course Code: PSIT402a
Periods per week (1 Period is 60 minutes) 4
Credits 4
Hours Marks
Evaluation System Theory Examination 2½ 60
Internal -- 40

Course Objectives:
 The prime objective of this course is to introduce the students to the field of Language
Computing and its applications ranging from classical era to modern context.
 To provide understanding of various NLP tasks and NLP abstractions such as
Morphological analysis, POS tagging, concept of syntactic parsing, semantic analysis
etc.
 To provide knowledge of different approaches/algorithms for carrying out NLP tasks.
 To highlight the concepts of Language grammar and grammar representation in
Computational Linguistics.

Unit Details Lectures Outcome
I Introduction to NLP, brief history, NLP applications:
Speech to Text(STT), Text to Speech(TTS), Story
Understanding, NL Generation, QA system, Machine
Translation, Text Summarization, Text classification,
Sentiment Analysis, Grammar/Spell Checkers etc.,
challenges/Open Problems, NLP abstraction levels,
Natural Language (NL) Characteristics and NL
computing approaches/techniques and steps, NL tasks:
Segmentation, Chunking, tagging, NER, Parsing, Word
Sense Disambiguation, NL Generation, Web 2.0
Applications : Sentiment Analysis; Text Entailment;
Cross Lingual Information Retrieval (CLIR). 12 CO1
II Text Processing Challenges, Overview of Language
Scripts and their representation on Machines using 12 CO2

Page 61

55 Character Sets, Language, Corpus and Application
Dependence i ssues, Segmentation: word
level(Tokenization), Sentence level. Regular
Expression and Automata Morphology, Types, Survey
of English and Indian Languages Morphology,
Morphological parsing FSA and FST, Porter stemmer,
Rule based and Paradigm based Morphology , Human
Morphological Processing, Machine Learning
approaches.
III Word Classes ad Part -of-Speech tagging(POS), survey
of POS tagsets , Rule based approaches (ENGTOWL),
Stochastic approaches(Probabilistic, N -gram and
HMM), TBL morphology, unknown word handling,
evaluation metrics: Precision/Recall/F -measure, error
analysis. 12 CO3
IV NL parsing basics, approaches: TopDown, BottomUp,
Overview of Grammar Formalisms: constituency and
dependency school, Grammar notations CFG, LFG,
PCFG, LTAG, Feature - Unification, overview of
English CFG, Indian Language Parsing in Paninian
Karaka Theory, CFG parsing using Earley’s and CYK
algorithms, Proba bilistic parsing, Dependency Parsing:
Covington algorithm, MALT parser, MST parser. 12 CO4
V Concepts and issues in NL, Theories and approaches
for Semantic Analysis, Meaning Representation, word
similarity, Lexical Semantics, word senses and
relationships, WordNet (English and IndoWordnet),
Word Sense Disambiguation: Lesk Algorithm Walker’s
algor ithm, Coreferences Resolution:Anaphora,
Cataphora. 12 CO5

Books and References:
Sr.
No. Title Author/s Publisher Edition Year
1. Handbook of Natural
Language Processing Indurkhya , N.,
& Damerau,
F. J. CRC Press
Taylor and
Francis Group 2nd 2010
2. Speech and Language
Processing Martin, J. H.,
& Jurafsky,
D. Pearson
Education
India 2nd 2013
3. Foundations of Statistical
Natural Language Processing
Manning,
Christopher
and Heinrich,
Schutze MIT Press
1st 1997
4. Natural Language Processing
With Python
Steven Bird,
Edward
Loper O'Reilly
Media
2nd 2016
5. Video Links

Page 62

56 1. http://www.nptelvideos.in/2012/11/natural -language -processing.html

M. Sc (Information Technology) Semester – IV
Course Name: Natural Language Processing Practical Course Code: PSIT4P2a
Periods per week (1 Period is 60 minutes) 4
Credits 2
Hours Marks
Evaluation System Practical Examination 2 50
Internal -- -

List of Practical:
10 practicals covering the entire syllabus must be performed. The detailed list of
practical will be circulated later in the official workshop.

Course Outcomes:
After completion of the course, a student should be able to:
CO1 : Students will get idea about know -hows, issues and challenge in Natural Language
Processing and NLP applications and their relevance in the classical and modern context.
CO2 : Student will get understanding of Computational techniques and approaches for
solving NLP problems and develop modules for NLP tasks and tools such as Morph
Analyzer, POS tagger, Chunker, Parser, WSD tool etc.
CO3 : Students will also be introduced to various grammar formalisms, which they can apply
in different fields of study.
CO4 : Students can take up project work or work in R&D firms working in NLP and its allied
areas.

CO5 : Student will be able to understand applications in different sectors

Page 63

57













PSIT402b: Digital Image Forensics
M. Sc (Information Technology) Semester – IV
Course Name: Digital Image Forensics Course Code: PSIT402b
Periods per week (1 Period is 60 minutes) 4
Credits 4
Hours Marks
Evaluation System Theory Examination 2½ 60
Internal -- 40

Course Objectives:

 To understand describe the origin of computer forensics and the relationship between
law enforcement and industry.
 Describe electronic evidence and the computing investigation process.
 Extracting Digital Evidence from Images and establishing them in court of Law.
 Enhanc ing images for investigation and various techniques to enhance images.
 Interpret and present Evidences in Court of Law.

Unit Details Lectures Outcome
I History of Forensic Digital Enhancement , Establishing
Integrity of Digital Images for Court , 12 CO1
II Digital Still and Video Cameras , Color Modes and
Channel Blending to Extract Detail 12 CO2
III Multiple Image Techniques , Fast Fourier Transform
(FFT) – Background Pattern Removal . 12 CO3
IV Contrast Adjustment Techniques , Advanced Processing
Techniques , Comparison and Measurement 12 CO4
V The Approach – Developing Enhancement Strategies
for Images Intended for Analysis , Digital Imaging in
the Courts , Interpreting and Presenting Evidence 12 CO5

Books and References:
Sr. No. Title Author/s Publisher Edition Year
1. Forensic Digital Image Brian Dalrymple, Jill CRC 2018

Page 64

58 Processing: Optimization
of Impression Evidence Smith Press
2. Forensic Uses of Digital
Imaging John C. Russ, Jens
Rindel, P. Lord Taylor &
Francis
Group 2nd 2016








M. Sc (Information Technology) Semester – III
Course Name: Digital Image Forensics Practical Course Code: PSIT4P2b
Periods per week (1 Period is 60 minutes) 4
Credits 2
Hours Marks
Evaluation System Practical Examination 2 50
Internal -- -


List of Practical:
10 practicals covering the entire syllabus must be performed. The detailed list of
practical will be circulated later in the official workshop.

Course Outcomes:
After completion of the course, a student should be able to:
CO1: Understand the basics of image forensics and techniques to establish their integrity
CO2: Understand different techniques for extracting detail from images.
CO3: Understand and apply various advanced techniques in image processing and to
compare and measure various parameters associated with them
CO4: Apply various enhancement strategies for digital images
CO5: Prepare the evidence to be acceptable in the court of law.

Page 65

59












PSIT402c: Advanced IoT
M. Sc (Information Technology) Semester – IV
Course Name: Advanced IoT Course Code: PSIT402c
Periods per week (1 Period is 60 minutes) 4
Credits 4
Hours Marks
Evaluation System Theory Examination 2½ 60
Internal -- 40

Course Objectives:

 To understand the latest developments in IoT
 To build smart IoT applications
 To leverage the applications of IoT in different technologies
 To build own IoT platform

Unit Details Lectures Outcome
I The Artificial Intelligence 2.0, IoT and Azure IoT Suite,
Creating Smart IoT Application 12 CO1
II Cognitive APIs, Consuming Microsoft Cognitive APIs,
Building Smarter Application using Cognitive APIs. 12 CO2
III Implementing Blockchain as a service, Capturing,
Analysing and Visualizing real -time data, Making
prediction with machine learning. 12 CO3
IV IoT and Microservices, Service Fabric, Build your own
IoT platform: Introduction, Building blocks for IoT
solution, Essentials for building your own platform,
Platform requirements, building the platform by
initializing cloud instance, installing basic software
stacks, securing instance and software, installing
node.js and Node -RED, Message broker. 12 CO4
V Building Critical components, configuring message
broker, creating REST interface, Rule engine and
authentication, documentation and testing, Introspection
on what we build and deliverables. 12 CO5

Page 66

60
Books and References:
Sr. No. Title Author/s Publisher Edition Year
1. IoT, AI, and Blockchain
for .NET - Building a
Next -Generation
Application from the
Ground Up Nishith Pathak
Anurag Bhandari Apress -- 2018
2. Microservices, IoT and
Azure Bob Familiar Apress -- 2015
3. Build your own IoT
Platform Anand Tamboli Apress -- 2019
4. Internet of Things
Architectures, Protocols
and Standards Simone Cirani
Gianluigi Ferrari
Marco Picone Luca
Veltri Wiley 1 2019

M. Sc (Information Technology) Semester – IV
Course Name: Advanced IoT Practical Course Code: PSIT4P2c
Periods per week (1 Period is 60 minutes) 4
Credits 2
Hours Marks
Evaluation System Practical Examination 2 50
Internal -- -

List of Practical:
10 practicals covering the entire syllabus must be performed. The detailed list of
practical will be circulated later in the official workshop.


Course Outcomes:
After completion of the course, a student should be able to:
CO1: Build smart IoT applications on Azure.
CO2: Use Microsoft cognitive APIs to build IoT applications.
CO3: Implement Blockchain in IoT.
CO4: Install and use microservices in IoT.
CO5: Build own IoT platform and use it in a customised way.

Page 67

61











PSIT402d: Cyber Forensics
M. Sc (Information Technology) Semester – IV
Course Name: Cyber Forensics Course Code: PSIT402d
Periods per week (1 Period is 60 minutes) 4
Credits 4
Hours Marks
Evaluation System Theory Examination 2½ 60
Internal -- 40

Course Objectives:
 Explain laws relevant to computer forensics
 Seize digital evidence from pc systems
 Recover data to be used as evidence
 Analyse data and reconstruct events
 Explain how data may be concealed or hidden

Unit Details Lectures Outcome
I Computer Forensics: The present Scenario, The
Investigation Process, Computers – Searching and
Seizing, Electronic Evidence, Procedures to be
followed by the first responder. 12 CO1
II Setting up a lab for Computer Forensics, Hard Disks
and File Systems, Forensics on Windows Machine,
Acquire and Duplicate Data 12 CO2
III Recovery of deleted files and partitions, Using Access
Data FTK and Encase for forensics Investigation,
Forensic analysis of Steganography and Image files,
Cracking Application passwords. 12 CO3
IV Capturing logs and correlating to the events, Network
Forensics – Investigating logs and Network traffic,
Investigating Wireless and Web Attacks. 12 CO4
V Email Tracking and Email Crime investigation. Mobile
Forensics, Reports of Investigation, Become an expert
witness. 12 CO5

Page 68

62 Books and References:
Sr. No. Title Author/s Publisher Edition Year
1. EC-Council CHFIv10
Study Guide -- EC-Council -- 2018
2. The official CHFI Exam
312-49 study Guide Dave Kleiman SYNGRESS -- 2007
3. Digital Forensics and
Incident Response Gerard Johansen Packt
Publishing -- 2020
4. Practical Cyber
Forensics Niranjan Reddy Apress -- 2019


M. Sc (Information Technology) Semester – IV
Course Name: Cyber Forensics Practical Course Code: PSIT4 P2d
Periods per week (1 Period is 60 minutes) 4
Credits 2
Hours Marks
Evaluation System Practical Examination 2 50
Internal -- -


List of Practical:
10 practicals covering the entire syllabus must be performed. The detailed list of
practical will be circulated later in the official workshop.


Course Outcomes:
After completion of the course, a student should be able to:
CO1: Investigate the cyber forensics with standard operating procedures.
CO2: Recover the data from the hard disk with legal procedure.
CO3: To recover and analyse the data using forensics tool
CO4: Acquire the knowledge of network analysis and use it for analysing the internet
attacks.
CO5: Able to investigate internet frauds done through various gadgets like mobile, laptops,
tablets and become a forensic investigator.

Page 69

63











PSIT403a : Deep Learning
M. Sc (Information Technology) Semester – IV
Course Name: Deep Learning Course Code: PSIT403a
Periods per week (1 Period is 60 minutes) 4
Credits 4
Hours Marks
Evaluation System Theory Examination 2½ 60
Internal -- 40

Course Objectives:
 To present the mathematical, statistical and computational challenges of building
neural networks
 To study the concepts of deep learning
 To enable the students to know deep learning techniques to support real -time
applications

Unit Details Lectures Outcome
I Applied Math and Machine Learning Basics: Linear
Algebra: Scalars, Vectors, Matrices and Tensors ,
Multiplying Matrices and Vectors , Identity and Inverse
Matrices, Linear Dependence and Span , norms, special
matrices and vectors, eigen decompositions.
Numerical Computation: Overflow and under fl ow,
poor conditioning, Gradient Based Optimization,
Constraint optimization. 12 CO1
II Deep Networks: Deep feedforward network ,
regularization for deep learning , Optimization for
Training deep models 12 CO2
III Convolutional Networks, Sequence Modelling,
Applications 12 CO3
IV Deep Learning Research: Linear Factor Models,
Autoencoders, representation learning 12 CO4
V Approximate Inference, Deep Generative Models 12 CO5

Books and References:
Sr. No. Title Author/s Publisher Edition Year

Page 70

64 1. Deep Learning Ian Goodfellow,
Yoshua Bengio,
Aaron Courvile An MIT
Press
book 1st 2016
2. Fundamentals of Deep
Learning Nikhil Buduma O’Reilly 1st 2017
3. Deep Learning: Methods
and Applications Deng & Yu Now
Publishers 1st 2013
4. Deep Learning CookBook Douwe Osinga O’Reilly 1st 2017




M. Sc (Information Technology) Semester – IV
Course Name: Deep Learning Practical Course Code: PSIT4P3a
Periods per week (1 Period is 60 minutes) 4
Credits 2
Hours Marks
Evaluation System Practical Examination 2 50
Internal -- -


List of Practical:
10 practicals covering the entire syllabus must be performed. The detailed list of
practical will be circulated later in the official workshop.

Course Outcomes:
After completion of the course, a student should be able to:
CO1 : Describes basics of mathematical foundation that will help the learner to understand
the concepts of Deep Learning.
CO2 : Understand and describe model of deep learning
CO3 : Design and implement various deep sup ervised learning architectures for text & image
data.
CO4 : Design and implement various deep learning models and architectures.
CO5 : Apply various deep learning techniques to design efficient algorithms for real -world
applications.

Page 71

65











PSIT403b: Remote Sensing
M. Sc (Information Technology) Semester – IV
Course Name: Remote Sensing Practical Course Code: PSIT403b
Periods per week (1 Period is 60 minutes) 4
Credits 4
Hours Marks
Evaluation System Theory Examination 2½ 60
Internal -- 40

Course Objectives:
 Attain a foundational knowledge and comprehension of the physical, computational,
and perceptual basis for remote sensing.
 Gain familiarity with a variety of physical, biological, and human geographic
applications of remote sensing.
 Gain basic experience in the hands -on application of remote sensing data through
visual interpretation and digital image processing exercises.
 Analyze and synthesize understanding by identifying and developing a research and
application pro posal using remote sensing.

Unit Details Lectures Outcome
I Remote Sensing: Basic Principles
Introduction, Electromagnetic Radiation and Its
Properties, Terminology, Nature of Electromagnetic
Radiation, The Electromagnetic Spectrum, Sources of
Electromagnetic Radiation, Interactions with the Earth's
Atmosphere, Interaction with Earth -Surface Mater ials,
Spectral Reflectance of Earth Surface Materials
Remote Sensing Platforms and Sensors
Introduction, Characteristics of Imaging Remote
Sensing Instruments, Spatial Resolution, Spectral
Resolution, Radiometric Resolution, Optical, Near -
infrared and Th ermal Imaging Sensors, Along -Track
Scanning Radiometer (ATSR), Advanced Very High
Resolution Radiometer (AVHRR) and NPOESS VIIRS, 12 CO1

Page 72

66 MODIS, Ocean Observing Instruments, IRS LISS,
Landsat Instruments, SPOT Sensors, Advanced
Spaceborne Thermal Emission and Refl ection
Radiometer (ASTER), High -Resolution Commercial
and Small Satellite Systems, Microwave Imaging
Sensors, European Space Agency Synthetic Aperture
Spaceborne Radars, Radarsat, TerraSAR -X and
COSMO/Skymed, ALOS PALSAR
II Hardware and Software Aspects of Digital Image
Processing
Introduction, Properties of Digital Remote Sensing
Data, Digital Data, Data Formats, System Processing,
Numerical Analysis and Software Accuracy, Some
Remarks on Statistics,
Preprocessing of Remo tely-Sensed Data
Introduction, Cosmetic Operations, Missing Scan Lines,
Destriping Methods, Geometric Correction and
Registration, Orbital Geometry Model, Transformation
Based on Ground Control Points, Resampling
Procedures, Image Registration, Other Ge ometric
Correction Methods, Atmospheric Correction,
Background, Image -Based Methods, Radiative Transfer
Models, Empirical Line Method, Illumination and View
Angle Effects, Sensor Calibration, Terrain Effects 12 CO2
III Image Enhancement Techniques
Introduction, Human Visual System, Contrast
Enhancement, Linear Contrast Stretch, Histogram
Equalization, Gaussian Stretch, Pseudocolour
Enhancement, Density Slicing, Pseudocolour
Transform,
Image Transforms
Introduction, Arithmetic Operations, Image Add ition,
Image Subtraction, Image Multiplication, Image
Division and Vegetation Indices, Empirically Based
Image Transforms, Perpendicular Vegetation Index,
Tasselled Cap (Kauth –Thomas) Transformation,
Principal Components Analysis, Standard Principal
Compon ents Analysis, Noise -Adjusted PCA,
Decorrelation Stretch, Hue -Saturation -Intensity (HSI)
Transform, The Discrete Fourier Transform, Two -
Dimensional Fourier Transform, Applications of the
Fourier Transform, The Discrete Wavelet Transform,
The One -Dimensiona l Discrete Wavelet Transform,
The Two -Dimensional Discrete Wavelet Transform,
Change Detection, Introduction, NDVI Difference
Image, PCA, Canonical Correlation Change Analysis,
Image Fusion, HSI Algorithm, PCA, Gram -Schmidt
Orthogonalization, Wavelet -Base d Methods, Evaluation
– Subjective Methods, Evaluation – Objective Methods 12 CO3
IV Filtering Techniques 12 CO4

Page 73

67 Spatial Domain Low -Pass (Smoothing) Filters, Moving
Average Filter, Median Filter, Adaptive Filters, Spatial
Domain High -Pass (Sharpening) Filters, Image
Subtraction Method, Derivative -Based Methods, Spatial
Domain Edge Detectors, Frequency Domain Filters
Classification : Geometrical Basis of Classification,
Unsupervised Classification, The k-Means Algorithm,
ISODATA, A Modified k-Means Algorithm,
Supervised Classification, Training Samples, Statistical
Classifiers, Neural Classifiers, Subpixel Classifi cation
Techniques, The Linear Mixture Model, Spectral Angle
Mapping, ICA, Fuzzy Classifiers, More Advanced
Approaches to Image Classification, Support Vector
Machines , Decision Trees , Other Methods of
Classification, Incorporation of Non -spectral Feature s,
Texture, Use of External Data, Contextual Information,
Feature Selection, Classification Accuracy
Advanced Topics
Introduction, SAR Interferometry, Basic Principles,
Interferometric Processing, Problems in SAR
Interferometry, Applications of SAR I nterferometry,
Imaging Spectroscopy, Processing Imaging
Spectroscopy Data, Lidar, Lidar Details, Lidar
Applications
V Environmental Geographical Information Systems :
A Remote Sensing Perspective, Definitions, The
Synergy between Remote Sensi ng and GIS, Data
Models, Data Structures and File Formats, Spatial Data
Models, Data Structures, File Formats, Raster to Vector
and Vector to Raster Conversion, Geodata Processing,
Buffering, Overlay, Locational Analysis, Slope and
Aspect, Proximity Analys is, Contiguity and
Connectivity, Spatial Analysis, Point Patterns and
Interpolation.
Relating Field and Remotely -Sensed Measurements :
Statistical Analysis, Exploratory Data Analysis and
Data Mining, Environmental Modelling, Visualization,
Multicriteria D ecision Analysis of Groundwater
Recharge Zones, Data Characteristics, Multicriteria
Decision Analysis, Evaluation, Assessing Flash Flood
Hazards by Classifying Wadi Deposits in Arid
Environments, Water Resources in Arid Lands, Case
Study from the Sinai Pen insula, Egypt, Optical and
Microwave Data Fusion, Classification of Wadi
Deposits, Correlation of Classification Results with
Geology and Terrain Data, Remote Sensing and GIS in
Archaeological Studies, Introduction, Homul
(Guatemala) Case Study, Aksum (E thiopia) Case Study
12 CO5

Page 74

68 Books and References:
Sr. No. Title Author/s Publisher Edition Year
1. Computer Processing of
Remotely -Sensed Images :
An Introduction Paul M. Mather ,
Magaly Koch Wiley -
Blackwell 4th 2011
2. Remote Sensing for
Geoscientists Image
Analysis and Integration Gary L. Prost CRC
Press 3rd 2014
3. Remote Sensing: Models
and Methods for Image
Processing Robert A.
Schowengerdt Elsevier 3rd 2007
4. Introductory Digital
Image Processing : A
Remote Sensing
Perspective John R. Jensen Pearson 2015

M. Sc (Information Technology) Semester – IV
Course Name: Remote Sensing Practical Course Code: PSIT4P3b
Periods per week (1 Period is 60 minutes) 4
Credits 2
Hours Marks
Evaluation System Practical Examination 2 50
Internal -- -



List of Practical:
10 practicals covering the entire syllabus must be performed. The detailed list of
practical will be circulated later in the official workshop.


Course Outcomes:
After completion of the course, a student should be able to:
CO1: Understand the basics of remote sensing and its various applications
CO2: Understand the Hardware and Software aspects of Digital Image Processing and
demonstrate various techniques in pre -processing data
CO3: Demonstrate various image enhanc ement and transformation techniques.
CO4: Understand and Demonstrate various filtering, classification techniques along with
advanced functionalities.
CO5: Perform comparison of Field and Remotely sensed measurements using various
techniques.

Page 75

69










PSIT403c: Server Virtualization on VMWare Platform
M. Sc (Information Technology) Semester – IV
Course Name: Server Virtualization on VMWare
Platform Course Code: PSIT403c
Periods per week (1 Period is 60 minutes) 4
Credits 4
Hours Marks
Evaluation System Theory Examination 2½ 60
Internal -- 40

Course Objectives:

 Identify the need for Server Virtualization
 Describe the components and features of vSphere 6.7 and ESXi
 Describe how VMware’s products help solve business and technical challenges with
regard to Server Virtualization

Unit Details Lectures Outcome
I Introducing VMware vSphere 6.7 : Exploring
VMware vSphere 6.7 , Examining the Products in the
vSphere Suite , Examining the Features in VMware
vSphere , Licensing VMware vSphere , Why Choose
vSphere?
Planning and Installing VMware ESXi : VMware
ESXi Architecture , Understanding the ESXi
Hypervisor , Examining the ESXi Components ,
Planning a VMware vSphere Deployment , Choosing a
Server Platform , Determining a Storage Architecture ,
Integrating with the Network Infrastructure , Deploying
VMware ESXi , Installing VMware ESXi Interactively ,
Performing an Unattended Installation of VMware
ESXi , Deploying VMware ESXi with vSphere Auto
Deploy , Performing Post -installation Configuration ,
Reconfi guring the Management Network , Using the
vSphere Host Client , Configuring Time
Synchronization , Configuring Name Resolution ,
Installing and Configuring vCenter Server : 12 CO1

Page 76

70 Introducing vCenter Server , C entralizing User
Authentication Using vCenter Single Sign -On,
Understanding the Platform Services Controller , Using
the vSphere Web Client for Administration , Providing
an Extensible Framework , Choosing the Version of
vCenter Server , Planning and Designing a vCenter
Server Deployment , Sizing Hardware for vCenter
Server , Planning for vCenter Server Availability ,
Running vCenter Server and Its Components as VMs ,
Installing vCenter Server and Its Components ,
Installing vCenter Server in an Enhanced Linked Mode
Group , Exploring vCenter Server , The vSphere Web
Client Home Screen , Using the Navigator , Creating and
Managing a vCenter Server Inventory , Understanding
Inventory Views and Objects , Creating and Adding
Inventory Objects , Exploring vCenter Server’s
Management Features , Understanding Basic Host
Management , Examining Basic Host Configuration ,
Using Scheduled Tasks , Using the Events and Events
Consoles in vCenter Server , Working with Host
Profiles , Tags and Custom Attributes , Managing
vCenter Server Settings , General vCenter Server
Settings , Licensing , Message of the Day , Advanced
Settings , Auto Deploy , vCenter HA , Key Management
Servers , Storage Providers , vSphere Web Client
Administration , Roles , Licensing , vCenter Solutions
Manager , System Configuration , VMware Appliance
Management Administration , Summary , Monitor ,
Access , Networking , Time , Services , Update ,
Administration , Syslog , Backup .
II vSphere Update Manager and the vCenter Support
Tools :
vSphere Update Manager , vSphere Update Manager
and the vCenter Server Appliance , Installing the Update
Manager Download Service , The vSphere Update
Manager Plug -in Contents , Reconfiguring the VUM or
UMDS , Installation with the Update Manager Utility ,
Upgrading VUM from a Previous Version ,
Configuring vSphere Update Manager , Creating
Baselines Routine Updates , Attaching and Detaching
Baselines or Baseline Groups , Performing a Scan ,
Staging Patches , Remediating Hosts , Upgrading
VMware Tools , Upgrading Host Extensions ,
Upgrading Hosts with vSphere Update Manager ,
Importing an ESXi Image and Creating the Host
Upgrade Baseline , Upgrading a Host , Upgrading VM
Hardware , Performing an Orchestrated Upgrade ,
Investigating Alternative Update Options , Using
vSphere Update Manager PowerCLI , Upgrading and
Patching without vSphere Update Manager , vSphere 12 CO2

Page 77

71 Auto Deploy , Deploying Hosts with Auto Deploy ,
vCenter Support Tools , ESXi Dump Collector ,
Other vCenter Support Tools . Creating and
Configuring a vSphere Network : Putting Together a
vSphere Network , Working with vSphere Standard
Switches , Comparing Virtual Switches and Physical
Switches , Understanding Ports and Port Groups ,
Understanding Uplinks , Configuring the Management
Network , Configuring VMkernel Networking , Enabling
Enhanced Multicast Function s, Configuring TCP/IP
Stacks , Configuring Virtual Machine Networking ,
Configuring VLANs , Configuring NIC Teaming , Using
and Configuring Traffic Shaping , Bringing It All
Together , Working with vSphere Distributed Switches ,
Creating a vSphere Distributed Switch , Removing an
ESXi Host from a Distributed Switch , Removing a
Distributed Switch , Managing Distributed Switches ,
Working with Distributed Port Groups , Managing
VMkernel Adapters , Using NetFlow on vSphere
Distributed Switches , Enabling Switch Discove ry
Protocols , Enabling Enhanced Multicast Functions ,
Setting Up Private VLANs , Configuring LACP ,
Configuring Virtual Switch Security , Understanding
and Using Promiscuous Mode , Allowing MAC Address
Changes and Forged Transmits .
III Creating and Configuring Storage Devices :
Reviewing the Importance of Storage Design ,
Examining Shared Storage Fundamentals , Comparing
Local Storage with Shared Storage , Defining Common
Storage Array Architectures , Explaining RAID ,
Understanding vSAN , Understanding Midrange and
External Enterprise Storage Array Design , Choosing a
Storage Protocol , Making Basic Storage Choices ,
Implementing vSphere Storage Fundamentals ,
Reviewing Core vSphere Storage Concepts ,
Understanding Virtual Volumes , SCs vs LUNs , Storage
Polici es, Virtual Volumes , W orking with VMFS
Datastores , Working with Raw Device Mappings ,
Working with NFS Datastores , Working with vSAN ,
Working with Virtual Machine –Level Storage ,
Configuration , Leveraging SAN and NAS Best
Practices
Ensuring High Availa bility and Business
Continuity : Understanding the Layers of High
Availability , Clustering VMs , Introducing Network
Load Balancin g Clusterin g, Introducing Windows
Server Failover Clustering , Implementing vSphere High
Availability , Understanding vSphere Hig h Availability
Clusters . Understanding vSphere High Availability’s
Core Components , Enabling vSphere HA , Configuring 12 CO3

Page 78

72 vSphere High Availability , Configuring vSphere HA
Groups, Rules, Overrides, and Orchestrated VM
Restart , Managing vSphere High Availability ,
Introducing vSphere SMP Fault Tolerance , Using
vSphere SMP Fault Tolerance with vSphere High
Availability , Examining vSphere Fault Tolerance , Use
Cases , Planning for Business Continuity , Providing
Data Protection , Recovering from Disasters , Using
vSphere Replication . Securing VMware vSphere :
Overview of vSphere Security , Securing ESXi Hosts ,
Working with ESXi Authentication , Controlling
Access to ESXi Hosts , Keeping ESXi Hosts Patched ,
Managing ESXi Host Permissions , Configuring ESXi
Host Logging , Securing the ESXi Boot Process ,
Reviewing Other ESXi Security Recommendations ,
Securing vCenter Serve r, Managing vSphere
Certificates , Working with Certificate Stores , Getting
Started with Certificate Management , Authenticating
Users with Single Sign -On, Understanding the vpxuser
Account , Managing vCenter Server Permissions ,
Configuring vCenter Server Appliance Logging ,
Securing Virtual Machines , C onfiguring a Key
Management Server for VM and VSAN Encryption ,
Virtual Trusted Platform Module , Configuring Netwo rk
Security Policies , Keeping VMs Patched .
IV Creating and Managing Virtual Machines :
Understanding Virtual Machines , Examining Virtual
Machines from the Inside , Examining Virtual Machines
from the Outside , Creating a Virtual Machine ,
Choosing Values for Your New Virtual Machine ,
Sizing Virtual Machines , Naming Virtual Machines ,
Sizing Virtual Machine Hard Disks , Virtual Machine
Graphics , Installing a Guest Operating System ,
Working with Installation Media , Using the Installation
Medi a, Working in the Virtual Machine Console ,
Installing VMware Tools , Installing VMware Tools in
Windows , Installing VMware Tools in Linux ,
Managing Virtual Machines , Adding or Registering
Existing VMs , Changing VM Power States , Removing
VMs , Deleting VMs , Modifying V irtual Machines ,
Changing Virtual Machine Hardware , Using Virtual
Machine Snapshots .
Using Templates and vApps : Cloning VMs , Creating
a Customization Specification , Cloning a Virtual
Machine , Introducing vSphere Instant Cloning ,
Creating Templa tes and Deploying Virtual Machines ,
Cloning a Virtual Machine to a Template , Deploying a
Virtual Machine from a Template , Using OVF
Templates , Deploying a VM from an OVF Template ,
Exporting a VM as an OVF Template , Examining OVF 12 CO4

Page 79

73 Templates , Using Content Li braries , Content Library
Data and Storage , Content Library Synchronization ,
Creating and Publishing a Content Library , Subscribing
to a Content Library , Operating Content Libraries ,
Working with vApps , Creating a vApp , Editing a vApp ,
Changing a vApp’s Power State , Cloning a vApp ,
Importing Machines from Other Environments ,
Managing Resource Allocation : Reviewing Virtual
Machine , Resource Allocation , Working with Virtual
Machine Memory , Understanding ESXi Advanced
Memory Technologies , Controlling Memory
Allocation , Managing Virtual Machine CPU
Utilization , Default CPU Allocation , Setting CPU
Affinity , Using CPU Reservations , Using CPU Limits ,
Using CPU Shares , Summarizing How Reservations,
Limits, and Shares Work with CPUs , Using Resource
Pools , Configuring Resource Pools , Understanding
Resource Allocation with Resource Pools , Regulating
Network I/O Utilization , Controlling Storage I/O
Utilization , Enabling Storage I/O Control , Configuring
Storage Resource Settings for a Virtual Machine , Using
Flash Storage .
V Balancing Resource Utilization : Comparing
Utilization with Allocation , Exploring vMotion ,
Examining vMotion Requirements , Performing a
vMotion Migration Within a Cluster , Ensuring
vMotion Compatibility , Using Per -Virtual -Machine
CPU Masking , Using Enhanced vMotion
Compatibility , Using Storage vMotion , Combining
vMotion with Storage vMotion , Cross -vCenter
vMotion , Examining Cross -vCenter vMotion
Requirements , Performing a Cross -vCenter Motion ,
Exploring vSphere Distributed Resource Sch eduler ,
Understanding Manual Automation Behavior ,
Reviewing Partially Automated Behavior , Examining
Fully Automated Behavior , Working with Distributed
Resource Scheduler Rules , Working with Storage DRS ,
Creating and Working with Datastore Clusters ,
Config uring Storage DRS .
Monitoring VMware vSphere Performance :
Overview of Performance Monitoring , Using Alarms
Understanding Alarm Scopes , Creating Alarms ,
Managing Alarms , Working with Performance Charts ,
Overview Layout , Advanced Layout , Work ing with
esxtop , Monitoring CPU Usage , Monitoring Memory
Usage , Monitoring Network Usage , Monitoring Disk
Usage .
Automating VMware vSphere : Why Use
Automation? vSphere Automation Automating with
PowerCLI , PowerShell and PowerCLI , What’s New in 12 CO5

Page 80

74 PowerC LI, Installing and Configuring PowerCLI on
Windows , Installing and Configuring PowerCLI on
macOS , Installing and Configuring PowerCLI on
Linux , Additional PowerCLI Capabilities Getting
Started with PowerCLI , Building PowerCLI Scripts ,
PowerCLI Advanced Capabilities , Additional
Resources .

Books and References:
Sr No Title Author/s Publisher Edition Year
1. Mastering VMware
vSphere 67 Nick Marshall , Mike
Brown , G Blair
Fritz , Ryan Johnson Sybex,
Wiley -- 2019
2. Mastering VMware
vSphere 67 Martin Gavanda ,
Andrea Mauro ,
Paolo Valsecchi ,
Karel Novak Packt -- 2019

M Sc (Information Technology) Semester – IV
Course Name: Server Virtualization on VMWare
Platform Practical Course Code: PSIT4P3c
Periods per week (1 Period is 60 minutes) 4
Credits 2
Hours Marks
Evaluation System Practical Examination 2 50
Internal -- -

List of Practical:
10 practicals covering the entire syllabus must be performed The detailed list of
practical will be circulated later in the official workshop


Course Outcomes:
After completion of the course, a student should be able to:
CO1: Understand VMWare VSphere 67, Install ESX i and Configure VSphere Centre
CO2: Demonstrate the use of VSphere Update Manager and Create a VSphere Network
CO3: Understand VSphere Security, Create and configure storage devices and Perform
configurations to ensure business continuity
CO4: Demonstrate Resource allocation, Creating and managing virtual machine and the use
of templates
CO5: Understand automation of vSphere and manage resource allocation

Page 81

75

















PSIT403d : Security Operations Centre
M. Sc (Information Technology) Semester – IV
Course Name: Security Operations Centre Course Code: PSIT403d
Periods per week (1 Period is 60 minutes) 4
Credits 4
Hours Marks
Evaluation System Theory Examination 2½ 60
Internal -- 40

Course Objectives:

 The SOC (Security Operations Centre) allows an organization to enforce and test its
security policies, processes, procedures and activities through one central platform
that monitors and evaluates the effectiveness of the individual elements and the
overall security system of the organization .
 This will also allow the learners to configure various use cases and detect various
attacks across the network and report them in real time and also take appropriate
actions.
 This course will cover the design, deployment and operation of the SOC.
 Once this course is completed, students will have the skills to perform your SOC
responsibilities effectively.

Unit Details Lectures Outcome
I Introduction to Security Operations Management
Foundation Topics Introduction to Identity and Access
Management Phases of the Identity and Access
Lifecycle Registration and Identity Validation
Privileges Provisioning Access Review Access
Revocation Password Management Password Creation 12 CO1

Page 82

76 Password Storage and Transmission
Password Reset Password Synchronization
Directo ry Management Single Sign -On
Kerberos Federated SSO Security Assertion Markup
Language OAuth OpenID Connect
Security Events and Logs Management
Logs Collection, Analysis, and Disposal
Syslog Security Information and Event Manager Assets
Management Assets I nventory Assets Ownership
Assets Acceptable Use and Return Policies Assets
Classification Assets Labeling Assets and Information
Handling Media Management
Introduction to Enterprise Mobility Management
Mobile Device Management
Configuration and Change Mana gement
Configuration Management Change Management
Vulnerability Management
Vulnerability Identification Finding Information about
a Vulnerability Vulnerability Scan Penetration
Assessment
Product Vulnerability Management
Vulnerability Analysis and Prioriti zation
Vulnerability Remediation Patch Management
References and Additional Readings
Fundamentals of Cryptography and Public Key
Infrastructure (PKI)
Cryptography Ciphers and Keys
Ciphers Keys Block and Stream Ciphers
Symmetric and Asymmetric Algorithms
Symmetric Algorithms Asymmetric Algorithms Hashes
Hashed Message Authentication Code Digital
Signatures
Digital Signatures in Action Key Management
Next -Generation Encryption Protocols
IPsec and SSL IPsec SSL Fundamentals of PKI Public
and Private Key Pair s RSA Algorithm, the Keys, and
Digital Certificates
Certificate Authorities Root and Identity Certificates
Root Certificate Identity Certificate X.500 and X.509v3
Certificates
Authenticating and Enrolling with the CA
Public Key Cryptography Standards
Simpl e Certificate Enrollment Protocol
Revoking Digital Certificates Using Digital Certificates
PKI Topologies Single Root CA
Hierarchical CA with Subordinate CAs
Cross -certifying CAs Exam Preparation Tasks
Review All Key Topics Complete Tables and Lists
from M emory
Introduction to Virtual Private Networks (VPNs)

Page 83

77 What Are VPNs? Site -to-site vs. Remote -Access VPNs
An Overview of IPsec IKEv1 Phase 1 IKEv1 Phase 2
IKEv2 SSL VPNs
SSL VPN Design Considerations User Connectivity
VPN Device Feature Set
Infrastructure Planning Implementation Scope
II Windows -Based Analysis
Process and Threads Memory Allocation
Windows Registration Windows Management
Instrumentation Handles Services
Windows Event Logs Exam Preparation Tasks
Linux - and Mac OS X –Based Analysis
Processes Forks Permissions Symlinks
Daemons UNIX -Based Syslog
Apache Access Logs
Endpoint Security Technologies
Antimalware and Antivirus Software
Host -Based Firewalls and Host -Based Intrusion
Prevention Application -Level Whitelisting and
Blacklisting Sy stem -Based Sandboxing
12 CO2
III Threat Analysis
What Is the CIA Triad: Confidentiality, Integrity, and
Availability?
Confidentiality Integrity Availability
Threat Modeling Defining and Analyzing the Attack
Vector Understanding the Attack Complexity Privileges
and User Interaction
The Attack Scope Exam Preparation Tasks
Forensics
Introduction to Cybersecurity Forensics
The Role of Attribution in a Cybersecurity
Investigation The Use of Digital Evidence
Defining Digital Forensic Evidence
Understanding Best, Corroborating, and Indirect or
Circumstantial Evidence
Collecting Evidence from Endpoints and Servers
Collecting Evidence from Mobile Devices Collecting
Evidence from Network Infrastructure Devices Chain
of Custody
Fundamentals of Microsoft Windows Forensics
Processes, Threads, and Services
Memory Management Windows Registry
The Windows File System Master Boot Record (MBR)
The Master File Table (MFT)
Data Area and Free Space FAT
NTFS MFT Timestamps, MACE, and Alternate Data
Streams EFI Fundamentals of Linux Forensics Linux
Processes Ext4
Journaling Linux MBR and Swap File System 12 CO3

Page 84

78 Exam Preparation Tasks
Fundamentals of Intrusion Analysis
Common Artifact Elements and Sources of Security
Events False Positives, False Negatives, True Positives,
and True Negatives
Understanding Regular Expressions
Protocols, Protocol Headers, and Intrusion Analysis
Using Packet Captures for Intrusion Analysis Mapping
Security Event Types to Source Technologies
IV Introduction to Incident Response and the Incident
Handling Process
Introduction to Incident Response
What Are Events and Incidents? The Incident Response
Plan The Incident Response Process
The Preparation Phase The Detection and Analysis
Phase Containment, Eradication, and Recovery Post -
Incident Activity (Postmortem) Information Sharing
and Coordination Incident Response Team Structure
The Vocabulary for Event Recording and Incident
Sharing (VERIS)
Incident Response Teams
Computer Security Incident Response Teams (CSIRTs)
Product Security Incident Response Teams (PSIRTs)
Security Vulnerabilities and Their Severity
Vulnerability Chaining Role in Fixing Prioritization
Fixing Theoretical Vulnerabilities Internally Versus
Externally Found Vulnerabilities National CSIRTs and
Computer Emergency Response T eams (CERTs)
Coordination Centers Incident Response Providers and
Managed Security Service Providers (MSSPs)
Compliance Frameworks
Payment Card Industry Data Security Standard (PCI
DSS) PCI DSS Data
Health Insurance Portability and Accountability Act
(HIPA A) HIPAA Security Rule HIPAA Safeguards
Administrative Safeguards Physical Safeguards
Technical Safeguards Sarbanes -Oxley (SOX) Section
302 Section 404 Section 409 SOX Auditing Internal
Controls
Network and Host Profiling
Network Profiling Throughput Meas uring Throughput
Used Ports Session Duration
Critical Asset Address Space Host Profiling
Listening Ports Logged -in Users/Service Accounts
Running Processes Applications 12 CO4
V The Art of Data and Event Analysis
Normalizing Data Interpreting Common Data Values
into a Universal Format Using the 5 -Tuple Correlation
to Respond to Security Incidents Retrospective
Analysis and Identifying Malicious Files Identifying a 12 CO5

Page 85

79 Malicious File Mapping Threat Intelligence with DNS
and Other Artifacts
Deterministic Versus Probabilistic Analysis
Intrusion Event Categories
Diamond Model of Intrusion
Cyber Kill Chain Model Reconnaissance
Weaponization Delivery Exploitation
Installation Command and Control Action and
Objectives
Types of Attacks and Vulnerabilities
Types of Attacks Reconnaissance Attacks
Social Engineering Privilege Escalation Attacks
Backdoors Code Execution
Man-in-the Middle Attacks Denial -of-Service Attacks
Direct DDoS Botnets Participating in DDoS Attacks
Reflected DDoS Attacks
Attack Methods for Data Exf iltration ARP Cache
Poisoning Spoofing Attacks Route Manipulation
Attacks Password Attacks
Wireless Attacks Types of Vulnerabilities
Security Evasion Techniques
Key Encryption and Tunneling Concepts
Resource Exhaustion Traffic Fragmentation
Protocol -Level Misinterpretation Traffic Timing,
Substitution, and Insertion Pivoting

Books and References:
Sr. No. Title Author/s Publisher Edition Year
1. CCNA Cyber Ops
SECOPS
210-255 Official Cert
Guide Omar Santos, Joseph
Muniz CISCO 1st 2017
2. CCNA Cyber Ops
SECFND 210 -250
Official Cert Guide Omar Santos, Joseph
Muniz CISCO 1st 2017
3. CCNA Cyber security
Operations Companion
Guide CISCO 1st 2018

M. Sc (Information Technology) Semester – IV
Course Name: Security Operations Centre Practical Course Code: PSIT4P3d
Periods per week (1 Period is 60 minutes) 4
Credits 2
Hours Marks
Evaluation System Practical Examination 2 50
Internal -- -

List of Practical:
10 practicals covering the entire syllabus must be performed. The detailed list of

Page 86

80 practical will be circulated later in the official workshop.

Course Outcomes:
After completion of the course, a student should be able to:
CO1: Understanding basics of SOC, Cryptography and managing and deploying VPNs.
CO2: Analyse Windows and Linux based logs along with logs generated by endpoints.
CO3: Understand and analyze various forms of intrusions, threats and perform forensic
analysis on them.
CO4: Understand the incident response process and handle incidents by adhering to
compliance policies and standards set by the organization.
CO5: Understand the various types of attacks and vulnerabilities, categorize events and
perform incident analysis.
PSIT404a: Human Computer Interaction
M. Sc (Information Technology) Semester – IV
Course Name: Human Computer Interaction Course Code: PSIT404a
Periods per week (1 Period is 60 minutes) 4
Credits 4
Hours Marks
Evaluation System Theory Examination 2½ 60
Internal -- 40

Course Objectives:

 Understand the important aspects of implementation of human -computer interfaces.
 Identify the various tools and techniques for interface analysis, design, and evaluation.
 Identify the impact of usable interfaces in the acceptance and performance utilization
of information systems

Unit Details Lectures Outcome
I The Interaction: Models of interaction, Design Focus,
Frameworks and HCI, Ergonomics, Interaction styles,
Elements of the WIMP interface,Interactivity
Paradigms: Introduction, Paradigms for interaction
Interaction design basics: What is design?, The
process of design, Us er focus, Cultural probes,
Navigation design, the big button trap, Modes, Screen
design and layout, Alignment and layout matters,
Checking screen colors, Iteration and prototyping
HCI in the software process : The software life cycle,
Usability engineering , Iterative design and prototyping,
Prototyping in practice, Design rationale 12 CO1
II Design : Principles to support usability, Standards,
Guidelines, Golden rules and heuristics, HCI patterns 12 CO2

Page 87

81 Implementation support: Elements of windowing
systems, Programming the application, Going with the
grain, Using toolkits, User interface management
systems
Evaluation techniques: What is evaluation?, Goals of
evaluation, Evaluation through expert analysis,
Evaluation through user participation, Choosing an
evaluation method
III Universal design: Universal design principles, Multi -
modal interaction, Designing websites for screen
readers, Choosing the right kind of speech, Designing
for diversity
User support: Requirements of user support,
Approaches to user support, Adaptive help systems,
Designing user support systems
Cognitive models: Goal and task hierarchies,
Linguistic models, The challenge of display -based
systems, Physical and device models, Cognitive
architectures 12 CO3
IV Socio -organizational issues and stakeholder
requirements: Organizational issues, Capturing
requirements
Communication and collaboration models: Face -to-
face communication, Conversation, Text -based
communication, Group working
Task analysis: Differences be tween task analysis and
other techniques, Task decomposition, Knowledge -
based analysis, Entity –relationship -based techniques,
Sources of information and data collection, Uses of task
analysis 12 CO4
V Dialog notations and design: What is dialog?, Dialog
design notations, Diagrammatic notations, Textual
dialog notations, Dialog semantics, Dialog analysis and
design
Models of the system: Standard formalisms,
Interaction models, Continuous behavior
Modeling rich interaction: Status –event analysis, Rich
contex ts, Low intention and sensor -based interaction 12 CO5

Books and References:
Sr. No. Title Author/s Publisher Edition Year
1. Human Computer
Interaction Alan Dix, Janet
Finlay, Gregory
Abowd, Russell
Beale Pearson
Education 3rd
2. Designing the User
Interface Shneiderman B.,
Plaisant C., Cohen
M., Jacobs S. Pearson 5th 2013

Page 88

82 Course Outcomes:
After completion of the course, a student should be able to:
CO1: have a clear understanding of HCI principles that influence a system’s interface
design, bef ore writing any code.
CO2: understand the evaluation techniques used for any of the proposed system.
CO3: understand the cognitive models and its design.
CO4: able to understand how to manage the system resources and do the task analysis.
CO5: able to design and implement a complete system.







PSIT404b : Advanced IoT
M. Sc (Information Technology) Semester – IV
Course Name: Advanced IoT Course Code: PSIT404b
Periods per week (1 Period is 60 minutes) 4
Credits 4
Hours Marks
Evaluation System Theory Examination 2½ 60
Internal -- 40

Course Objectives:

 To understand the applications on image processing in different disciplines.
 To apply the concepts to new areas of research in Image processing.


Unit Details Lectures Outcome
I Fuzzy Approaches and Analysis in Image Processing,
Text information extraction from images, Image and
Video steganography based on DCT and wavelet
transform. 12 CO1
II Zernike -Moments -Based Shape Descriptors for Pattern
Recognition and Classification Applications, An Image
De-Noising Method Based on Intensity Histogram
Equalization Technique for Image Enhancement, A
New Image Encryption Method Based on Improved
Cipher Block Chaining with Optimization Technique 12 CO2
III A Technique to Approximate Digital Planar Curve with
Polygon, Shape Determination of Aspired Foreign
Body on Pediatric Radiography Images Using Rule -
Based Approach, Evaluation of Image Detection and
Description Algorithms for Application in Monocular 12 CO3

Page 89

83 SLAM, Diophantine Equations for Enhanced Security
in Watermarking Scheme for Image Authentication
IV Design, Construction, and Programming of a Mobile
Robot Controlled by Artificial Vision, Review and
Applications of Multimodal Biometrics for Secured
Systems, Background Subtracti on and Object Tracking
via Key Frame -Based Rotational Symmetry Dynamic
Texture, A Novel Approach of Human Tracking
Mechanism in Wireless Camera Networks 12 CO4
V Digital Image Steganography: Survey, Analysis, and
Application, Vegetation Index: Ideas, Methods,
Influences, and Trends, Expert System through GIS -
Based Cloud 12 CO5





Books and References:
Sr. No. Title Author/s Publisher Edition Year
1. Advanced Image
Processing Techniques
and Applications N. Suresh Kumar,
Arun Kumar
Sangaiah, M. Arun,
S. Anand IGI
global -- 2017

Course Outcomes:

After completion of the course, a student should be able to:

CO01: Understand the advanced applications of Image processing.

CO02: Understand the application of image processing pattern recognition, encryption and
image enhancement.

CO03: Understand and apply the image processing techniques in identification of foreign
body using radiography, watermarking techniques.

CO04: Apply t he image processing techniques to robot vision, biometrics, human tracking
using wireless camera.

CO05: Apply image processing in steganography, expert systems through GIS based cloud.

Page 90

84
















PSIT404c : Storage as a Service
M. Sc (Information Technology) Semester – IV
Course Name: Storage as a Service Course Code: PSIT404c
Periods per week (1 Period is 60 minutes) 4
Credits 4
Hours Marks
Evaluation System Theory Examination 2½ 60
Internal -- 40

Course Objectives:

 Understand the need for Storage Area Network and Data protection to satisfy the
information explosion requirements.
 Study storage technologies: SAN, NAS, IP storage etc., which will bridge the gap
between the emerging trends in industry and academics.
 To get an insight of Storage area network architecture, protocols and its infrastructure.
 To study and discuss the applications of SAN to fulfill the needs of the storage
management in the heterogeneous environment.
 Study and understand the management of Stora ge Networks
 To understand different techniques of managing store.

Unit Details Lectures Outcome
I Introduction to Information Storage
Information Storage Data Types of Data Big Data
Information Storage Evolution of Storage Architecture
Data Center Infrastructure Core Elements of a Data
Center Key Characteristics of a Data Center Managing
a Data Center Virtualization and Cloud Computing
Data Center Environment
Application Database Management System (DBMS)
Host (Compute) Operating System 12 CO1

Page 91

85 Memory Vi rtualization Device Driver 20
Volume Manager File System Compute Virtualization
Connectivity Physical Components of Connectivity
Interface Protocols IDE/ATA and Serial ATA 28
SCSI and Serial SCSI Fiber Channel
Internet Protocol (IP) Storage
Disk Drive C omponents Platter Spindle Read/Write
Head Actuator Arm Assembly Drive Controller Board
Physical Disk Structure Zoned Bit Recording Logical
Block Addressing Disk Drive Performance Disk
Service Time Seek Time Rotational Latency Data
Transfer Rate D isk I/O Controller Utilization Host
Access to Data Direct -Attached Storage DAS Benefit
and Limitations Storage Design Based on Application
Requirements and Disk Performance Disk Native
Command Queuing
Introduction to Flash Drives Components and
Archit ecture of Flash Drives Features of Enterprise
Flash Drives Concept in Practice: VMware ESXi
Data Protection: RAID
RAID Implementation Methods Software RAID
Hardware RAID Array Components RAID
Techniques Striping
Mirroring Parity RAID Levels RAID 0
RAID 1 Nested RAID RAID 3 RAID 4
RAID 5 RAID 6 RAID Impact on Disk Performance
Application IOPS and RAID Configurations RAID
Comparison Hot Spares
II Intelligent Storage Systems Components of an
Intelligent Storage System Front End Cache Structure
of Cache Read Operation with Cache Write Operation
with Cache Implementation Cache Management
Cache Data Protection Back End Physical Disk Storage
Provisioning Traditional Storage Prov isioning LUN
Expansion: MetaLUN Virtual Storage Provisioning 82
Comparison between Virtual and Traditional
Storage Provisioning Use Cases for Thin and
Traditional LUNs LUN Masking
Types of Intelligent Storage Systems High -End
Storage Systems Midrange Sto rage Systems
Fiber Channel Storage Area Networks Fiber
Channel: Overview The SAN and Its Evolution
Components of FC SAN Node Ports Cables and
Connectors Contents
Interconnect Devices SAN Management Software FC
Connectivity Point -to-Point
Fiber Channel A rbitrated Loop Fiber Channel Switched
Fabric FC -SW Transmission
Switched Fabric Ports Fiber Channel Architecture Fiber
Channel Protocol Stack 12 CO2

Page 92

86 FC-4 Layer FC -2 Layer FC -1 Layer FC -0 Layer Fiber
Channel Addressing World Wide Names FC Frame
110. Structure an d Organization of FC Data Flow
Control
BB_Credit EE_Credit Classes of Service
Fabric Services Switched Fabric Login Types Zoning
Types of Zoning FC SAN Topologies Mesh Topology
Core -Edge Fabric Benefits and Limitations of Core -
Edge Fabric Virtualization in SAN Block -level
Storage Virtualization Virtual SAN (VSAN)
IP SAN and FCoE iSCSI Components of iSCSI iSCSI
Host Connectivity iSCSI Topologies Native iSCSI
Connectivity
Bridged iSCSI Connectivity Combining FC and Native
iSCSI Connectivity iSCSI Proto col Stack iSCSI PDU 6
iSCSI Discovery iSCSI Names iSCSI Session iSCSI
Command Sequencing FCIP FCIP Protocol Stack
FCIP Topology FCIP Performance and Security FCoE
I/O Consolidation Using FCoE Components of an
FCoE Network
Converged Network Adapte r Cables
FCoE Switches FCoE Frame Structure
FCoE Frame Mapping FCoE Enabling Technologies
Priority -Based Flow Control (PFC) Enhanced
Transmission Selection (ETS
Congestion Notification (CN)
Data Center Bridging Exchange Protocol (DCBX) 1
III Network -Attached Storage General -Purpose Servers
versus NAS Devices
Benefits of NAS File Systems and Network File
Sharing Accessing a File System
Network File Sharing Components of NAS
NAS I/O Operation NAS Implementations
Unifi ed NAS Unifi ed NAS Co nnectivity 164
Gateway NAS Gateway NAS Connectivity
Scale -Out NAS Scale -Out NAS Connectivity
NAS File -Sharing Protocols NFS CIFS
Factors Affecting NAS Performance File -Level
Virtualization
Object -Based and Unified Storage
Object -Based Storage Devices Object -Based Storage
Architecture Components of OSD Object Storage and
Retrieval in OSD
Benefits of Object -Based Storage
Common Use Cases for Object -Based Storage Content -
Addressed Storage CAS Use Cases
Healthcare Solution: Storing Patient Studies
Finance Solution: Storing Financial Records Unified
Storage Components of Unifi ed Storage Data Access
from Unified Storage 12 CO3

Page 93

87 Introduction to Business Continuity
Information Availability
Causes of Information Unavailability
Cons equences of Downtime
Measuring Information Availability
BC Terminology BC Planning Life Cycle
Failure Analysis Single Point of Failure
Resolving Single Points of Failure Multipathing
Software Business Impact Analysis BC Technology
Solutions
I/O Oper ation without PowerPath I/O Operation with
PowerPath Automatic Path Failover Path Failure
without PowerPath
Path Failover with PowerPath: Active -Active Array
Path Failover with PowerPath: Active -Passive Array
Backup and Archive
Backup Purpose Disaster Re covery Operational
Recovery Archival Backup Considerations Backup
Granularity Recovery Considerations Backup Methods
6 Backup Architecture Backup and Restore Operations
Backup Topologies Backup in NAS Environments
Server -Based and Serverless Backu p NDMP -Based
Backup
Backup Targets Backup to Tape Physical Tape Library
Limitations of Tape 2 Backup to Disk Backup to
Virtual Tape Virtual Tape Library Data Deduplication
for Backup Data Deduplication Methods Data
Deduplication Implementation Source -Based Data
Deduplication Target -Based Data Deduplication
Backup in Virtualized Environments Data Archive
Archiving Solution Architecture Use Case: E -mail
Archiving Use Case: File Archiving
IV Local Replication Replication Terminology Uses of
Local Replicas Replica Consistency Consistency of a
Replicated File System
Consistency of a Replicated Database
Local Replication Technologies
Host -Based Local Replication
LVM -Based Replication Advantages of LVM -Based
Replication L imitations of LVM -Based Replication File
System Snapshot
Storage Array -Based Local Replication
Full-Volume Mirroring Pointer -Based, Full -Volume
Replication Pointer -Based Virtual Replication
Network -Based Local Replication
Continuous Data Protection CDP Local Replication
Operation Tracking Changes to Source and Replica
Restore and Restart Considerations Creating Multiple
Replicas
Local Replication in a Virtualized Environment Remote 12 CO4

Page 94

88 Replication Modes of Remote Replication Remote
Replication Technologies Host -Based Remote
Replication LVM -Based Remote Replication Host -
Based Log Shipping Storage Array -Based Remote
Replication Synchronous Replication Mode
Asynchronous Replication Mode Disk -Buffered
Replication Mode Network -Based Remote Replication
CDP Remote Replication
Three -Site Replication Three -Site Replication —
Cascade/Multihop Synchronous + Asynchronous
Synchronous + Disk Buffered
Three -Site Replication — Triangle/Multitarget Data
Migration Solutions Remote Replication and Migration
in aVirtualized En vironment
Cloud Computing Cloud Enabling Technologies
Characteristics of Cloud Computing Benefits of Cloud
Computing
Cloud Service Models Infrastructure -as-a-Service
Platform -as-a-Service Software -as-a-Service Cloud
Deployment Models
Public Cloud Priva te Cloud Community Cloud Hybrid
Cloud Cloud Computing Infrastructure Physical
Infrastructure Virtual Infrastructure Applications and
Platform Software Cloud Management and Service
Creation Tools Cloud Challenges
Challenges for Consumers Challenges for Pro viders
Cloud Adoption Considerations
V Securing the Storage Infrastructure
Information Security Framework Risk Triad
Assets Threats Vulnerability Storage Security Domains
Securing the Application Access Domain Controlling
User Access to Data Protecting the Storage
Infrastructure 341
Data Encryption Securing the Management Access
Domain Controlling Administrative Access Protecting
the Management Infrastructure Securing Backup,
Replication, and Archive Security Implementations in
Storage Networking FC SAN FC SAN Security
Architecture Basic SAN Security Mechanisms LUN
Masking and Zoning
Securing Switch Ports Switch -Wide an d Fabric -Wide
Access Control
Logical Partitioning of a Fabric: Virtual SAN
NAS NAS File Sharing: Windows ACLs
NAS File Sharing: UNIX Permissions
NAS File Sharing: Authentication and Authorization
Kerberos Network -Layer Firewalls IP SAN Securing
Storage Infrastructure in Virtualized and Cloud
Environments Security Concerns
Security Measures Security at the Compute Level 12 CO5

Page 95

89 Security at the Network Level Security at the Storage
Level Concepts in Practice: RSA and VMware Security
Products RSA Secure ID RSA Id entity and Access
Management
RSA Data Protection Manager VMware vShield
Managing the Storage Infrastructure
Monitoring the Storage Infrastructure
Monitoring Parameters Components Monitored Hosts
Storage Network Storage
Monitoring Examples Accessibility Monitoring
Capacity Monitoring Performance Monitoring Security
Monitoring Alerts
Storage Infrastructure Management Activities
Availability Management Capacity Management
Performance Management Security Management
Reporti ng Storage Infrastructure Management in a
Virtualized Environment Storage Management
Examples
Storage Allocation to a New Server/Host
File System Space Management Chargeback Report
Storage Infrastructure Management Challenges
Developing an Ideal Solution 384Storage Management
Initiative Enterprise Management Platform Information
Lifecycle Management Storage Tiering Intra -Array
Storage Tiering Inter -Array Storage Tiering

Books and References:
Sr. No. Title Author/s Publisher Edition Year
1. Information Storage and
Management: Storing,
Managing, and Protecting
Digital Information in
Classic, Virtualized, and
Cloud Environments EMC John
Wiley &
Sons 2nd 2012


Course Outcomes:

After completion of the course, a student should be able to:

CO1: Understand different techniques of storage and RAID Technologies
CO2: Understand different intelligent storage technologies. Also, understand the benefits of
Fibre Channel Storage Networks along with iSCSI.
CO3: Understand the architecture of NAS and deployment along with Object based and
unified storage technologies. Also, the learner will be able to configure the storage devices to
maintain highest level of availability
CO4: Understand Replication and Migration techniques and implement them.
CO5: Understand Different techniques for managing and securing storage infrastructure.

Page 96

90















PSIT404d : Information Security Auditing
M. Sc (Information Technology) Semester – IV
Course Name: Information Security Auditing Course Code: PSIT404d
Periods per week (1 Period is 60 minutes) 4
Credits 4
Hours Marks
Evaluation System Theory Examination 2½ 60
Internal -- 40

Course Objectives:

 Understand various information security policies in place.
 Assess an organization based on the needs and suggest the requisite information
security policies to be deployed.
 Audit the organization across relevant policies and assist the organization in
implementing such policies along with suggesting improvements.

Unit Details Lectures Outcome
I Secrets of a Successful Auditor
Understanding the Demand for IS Audits
Understanding Policies, Standards, Guidelines, and
Procedures Understanding Professional Ethics
Understanding the Purpose of an Audit Differentiating
between Auditor and Auditee Roles Implementing Audit
Standards Auditor Is an Executive Position Understanding
the Corporate Organizational Structure
Governance
Strategy Planning for Organizational Control
Overview of Tactical Management Planning and
Performance Overview of Business Process Reengineeri ng
Operations Management Summary
Audit Process 12 CO1

Page 97

91 Understanding the Audit Program Establishing and
Approving an Audit Charter
Preplanning Specific Audits Performing an Audit Risk
Assessment Determining Whether an Audit Is Possible
Performing the Audit
Gather ing Audit Evidence Conducting Audit Evidence
Testing Generating Audit Findings
Report Findings Conducting Follow -up (Closing Meeting)
II Information Systems Acquisition and Development
Project Governance and Management
Business Case and Feasibility Analysis
System Development Methodologies
Control Identification and Design
Testing Methodologies
Configuration and Release Management
System Migration, Infrastructure Deployment and Data
Conversion
Post-implementation Review 12 CO2
III Information Systems Operations
Introduction
Common Technology Components
IT Asset Management
Job Scheduling and Production Process Automation
System Interfaces
End-user Computing
Data Governance
Systems Performance Management
Problem and Incident Management
Change, Co nfiguration, Release and
IT Service Level Management
Database Management
Business Resilience
Business Impact Analysis
Data Backup, Storage and Restoration
Business Continuity Plan
Disaster Recovery Plans 12 CO3
IV Information Systems Life Cycle
Governance in Software Development
Management of Software Quality
Overview of the Executive Steering Committee Change
Management
Management of the Software Project
Overview of the System Development Life Cycle
Overview of Data Architecture
Decision Support Systems Program Architecture
Centralization vs. Decentralization Electronic Commerce
System Implementation and Operations
Understanding the Nature of IT Services
Performing IT Operations Management
Performing Capacity Management 12 CO4

Page 98

92 Using Administrative Prote ction
Performing Problem Management
Monitoring the Status of Controls
Implementing Physical Protection
V Protecting Information Assets
Understanding the Threat
Using Technical Protection
Business Continuity and Disaster Recovery
Debunking the Myths Understanding the Five Conflicting
Disciplines Called Business Continuity Defining Disaster
Recovery Defining the Purpose of Business Continuity
Uniting Other Plans with Business Continuity
Understanding the Five Phases of a Business Continuity
Program Un derstanding the Auditor Interests in BC/DR
Plans 12 CO5



Books and References:
Sr. No. Title Author/s Publisher Edition Year
1. CISA®: Certified Information
Systems Auditor David Cannon SYBEX Fourth
Edition 2016
2. CISA Review Manual 27th
Edition ISACA 2019
3. CISA Certified Information
Systems Auditor All -in-One
Exam Guide, Fourth Edition, O’Reilly 4th
Edition 2019


Course Outcomes:

After completion of the course, a student should be able to:

CO1: Understand various information security policies and process flow, Ethics of an
Information security Auditor.

CO2: Understand various information systems in an organization, their criticality and various
governance and management policies associated with them.

CO3: Critically analyse various operational strategies like asset management, data
governance etc. and suggest requisite changes as per organizations requirements with
improvements.

CO4: Understand the information flow across the organization and identify the weak spots,
and also suggest improvements to strengthen them.

CO5: Come up with strong strategies to protect information assets and come up with an
efficient business continuity plan, disaster recovery strategy etc.

Page 99

93














PSIT4P4: Project Implementation and Viva
M. Sc (Information Technology) Semester – IV
Course Name: Project Implementation and Viva Course Code: PSIT4P4
Periods per week (1 Period is 60 minutes) 4
Credits 2
Hours Marks
Evaluation System Practical Examination 2 50
Internal -- -

The project dissertation and Viva Voce details are given in Appendix 1.

Page 100

94














Evaluation Scheme
Internal Evaluation (40 Marks)
The internal assessment marks shall be awarded as follows:
1. 30 marks (Any one of the following):
a. Written Test or
b. SWAYAM (Advanced Course) of minimum 20 hours and certification
exam completed or
c. NPTEL (Advanced Course) of minimum 20 hours and certification exam
completed or
d. Valid International Certifications (Prometric , Pearson, Certiport,
Coursera, Udemy and the like)
e. One certification marks shall be awarded one course only. For four
courses, the students will have to complete four certifications.
2. 10 marks
The marks given out of 40 (30 in Semester 4) for publishing th e research paper
should be divided into four course and should awarded out of 10 in each of the
four course.

i. Suggested format of Question paper of 30 marks for the written test.
Q1. Attempt any two of the following: 16
a.
b.
c.
d.

Q2. Attempt any two of the following: 14
a.
b.
c.
d.

ii. 10 marks from every course coming to a total of 40 marks, shall be awarded on
publishing of research paper in UGC approved / Other Journal with plagiarism

Page 101

95 less than 10%. The marks can be awarded as per the impact factor of the
journal, quality of the paper, importance of the contents published, social value.





External Examination: (60 marks)

All questions are compulsory
Q1 (Based on Unit 1) Attempt any two of the following: 12
a.
b.
c.
d.

Q2 (Based on Unit 2) Attempt any two of the following: 12
Q3 (Based on Unit 3) Attempt any two of the following: 12
Q4 (Based on Unit 4) Attempt any two of the following: 12
Q5 (Based on Unit 5) Attempt any two of the following: 12

Practical Evaluation (50 marks)

A Certified copy of hard -bound journal is essential to appear for the practical
examination.

1. Practical Question 1 20
2. Practical Question 2 20
3. Journal 5
4. Viva Voce 5

OR

1. Practical Question 40
2. Journal 5
3. Viva Voce 5

Project Documentation and Viva Voce Evaluation
The documentation should be checked for plagiarism and as per UGC guidelines, should be
less than 10%.

1. Documentation Report (Chapter 1 to 4) 20
2. Innovation in the topic 10
3. Documentation/Topic presentation and viva voce 20

Project Implementation and Viva Voce Evaluation

Page 102

96 1. Documentation Report (Chapter 5 to last) 20
2. Implementation 10
3. Relevance of the topic 10
4. Viva Voce 10

Appendix – 1
Project Documentation and Viva -voce (Semester III) and
Project Implementation and Viva -Voce (Semester IV)


Goals of the course Project Documentation and Viva -Voce

The student should:
 be able to apply relevant knowledge and abilities, within the main field of study, to a
given problem
 within given constraints, even w ith limited information, independently analyse and
discuss complex inquiries/problems and handle larger problems on the advanced level
within the main field of study
 reflect on, evaluate and critically review one’s own and others’ scientific results
 be abl e to document and present one’s own work with strict requirements on structure,
format, and language usage
 be able to identify one’s need for further knowledge and continuously develop one’s own
knowledge

To start the project:
 Start thinking early in the programme about suitable projects.
 Read the instructions for the project.
 Attend and listen to other student ´s final oral presentations.
 Look at the finished reports .
 Talk to senior master students.
 Attend possible information events (workshops / seminars / conferences etc.) about the
related topics .

Application and approval:
 Read all the detailed information about project.
 Finalise finding a place and supervisor.
 Check with the coordinator about subject/project, place and supervisor.
 Write the project proposal and plan along with the supervisor.
 Fill out the application together with the supervisor.
 Hand over the complete application , proposal and plan to the coordinator.
 Get an acknowledgement and approval f rom the coordinator to start the project.


During the project :
 Search, gather and read information and literature about the theory.

Page 103

97  Document well the practical work and your results.
 Take part in seminars and the running follow -ups/supervision.
 Think early on about disposition and writing of the final report.
 Discuss your thoughts with the supervisor and others.
 Read the SOP and the rest you need again.
 Plan for and do the mid -term reporting to the coordinator/examiner.
 Do a mid -term report also at the work -place (can be a requirement in some work -places).
 Write the first draft of the final report and rewrite it based on feedback from the
supervisor and possibly others.
 Plan for the final presentation of the report.

Finishing the project :
 Finish the report and obtain an OK from the supervisor.
 Ask the supervisor to send the certificate and feedback form to the coordinator .
 Attend the pre-final oral presentation arranged by the Coordinator .
 Rewrite the final report again based on feedback from the opponents and possibly others.
 Prepare a title page and a popular science summary for your report.
 Send the completed final report to the coordinator (via plagiarism software)
 Rewrite the report based on possible feedback from the coordinator .
 Appear for the final exam.

Project Proposal /research plan
 The student should spend the first 1 -2 weeks writing a 1 -2 pages project plan containing:
- Short background of the project
- Aims of the project
- Short description of methods that will be used
- Estimated time schedule for the project
 The research plan should be handed in to the supervisor and the coordinator.
 Writing the project plan will help you plan your project work and get you started in
finding information and understanding of methods needed to perform the project .

Project Documentation
The documentation should contain:
 Introduction - that should contain a technical and social (when possible) motivation of the
project topic .
 Description of the problems/to pics.
 Status of the research/knowledge in the field and literature review.
 Description of the methodology/approach. (The actual structure of the chapters here
depends on the topic of the documentation .)
 Results - must always contain analyses of results and associated uncertainties.
 Conclusions and proposals for the future work.
 Appendices (when needed).
 Bibliography - references and links.

For the master’s documentation, the chapters cannot be dictated, they may vary
according to the type of project. Howev er, in Semester III Project Documentation and
Viva Voce must contain at least 4 chapters (Introduction , Review of Literature,
Methodology / Approach, Proposed Design / UI design, etc. depending on the type of
project.) The Semester III repo rt should be spi ral bound.

Page 104

98
In Semester IV, the remaining Chapters should be included (which should include
Experiments performed, Results and discussion, Conclusions and proposals for future
work, Appendices) and Bibliography - references and links . Semester IV report should
include all the chapters and should be hardbound.