Academic Council
Item No: ________________
UNIVERSITY OF MUMBAI
Syllabus for SemV&VI
Program: Bachelor of Science
Course: Computer Science
Credit Based Semester and Grading System w ith
effect from
Academic Year 2018 -2019
Preamble
This is the third year curriculum in the subject of Computer Science. The revised structure is
designed to transform students into technically competent, socially responsible and ethical Computer
Science professionals. In these Semesters we have made the advancements in the subject based on
the previous Semesters Knowledge.
In the first year basic foundation of important skills required for software development is laid.
Second year of this course is about studying core computer science subjects . The third year is the
further advancement which covers developing capabilities to design formulations of computing
models and its applications in diverse area s.
The proposed curriculum contains two semesters, e ach Semester contains two Electives: Elective -I
and II. Every E lective contains three papers based on specific areas of Computer Science. It also
includes one Skill E nhanc ement paper per semester, helps the student to evaluate his/her computer
science domain specific skills and also to meet industry expectations . This revised curriculum has not
only taken the specific areas of computer science into consideration but will also give the opportunity
to the student to prove his/her ability in the subject practically through the Project Implementation . In
Semester V and Semester VI student has to under take a Project. It can boost his/her confidence and
also can encourage the student to perform innovati ons in the subject as the choice of the Project topic
is kept open covering most of the areas of Computer Science subject as per the students interest and
the subj ect they have learned during the Course .
Proposed Curriculum contains challenging and varied subject s aligned with the current trend with the
introduction of Machine Intelligence specific subject such as Artificial Intelligence, Information
Retrieval. Data Management related subjects such as Cloud Computing and Data Science. Image
processing topics such as Game Programming, Digital Image Processing. Introduction of physical
world through Architecting of IoT and Wireless Sensor Networks and Mobile Communication .
Security domain is also evolved by the introduction of Ethical Hacking, Cyber Forensic and
Information and Network Security. To get the hands on experience Linux Server Administration and
Web Services topics are included.
In essence, the objective of this syllabus is to create a pool of technologically savvy, theoretically
strong, innovati vely skilled and ethically responsible generation of computer science professionals.
Hope that the teacher and student community of University of Mumbai will accept and appreciate the
efforts.
T.Y.B.Sc. (Semester V and VI)
Computer Science Syllabus
Credit Based Semester and Grading System
To be implemented from the Academic year 201 8-2019
SEMESTER V
Course TOPICS Credits L / Week
Elective -I (Select Any Two)
USCS501 Artificial Intelligence 3 3
USCS502 Linux Server Administration 3 3
USCS503 Software Testing and Quality Assurance 3 3
Elective -II (Select Any Two)
USCS504 Information and Network Security 3 3
USCS505 Architecting of IoT 3 3
USCS506 Web Services 3 3
Skill Enhancement
USCS507 Game Programming 2 3
Practical
USCS P501 Practical of Elective -I 2 6
USCSP502 Practical of Elective -II 2 6
USCSP503 Project Implementation 1 3
USCSP504 Practical of Skill Enhanc ement : USCS507 1 3
SEMESTER VI
Course TOPICS Credits L / Week
Elective -I (Select Any Two)
USCS6 01 Wireless Sensor Networks and Mobile
Communication 3 3
USCS6 02 Cloud Computing 3 3
USCS6 03 Cyber Forensic s 3 3
Elective -II (Select Any Two)
USCS6 04 Information Retrieval 3 3
USCS6 05 Digital Image Processing 3 3
USCS6 06 Data Science 3 3
Skill Enhancemen t
USCS607 Ethical Hacking 2 3
Practical
USCS P601 Practical of Elective -I 2 6
USCSP6 02 Practical of Elective -II 2 6
USCSP6 03 Project Implementation 1 3
USCSP604 Practical of Skill Enhanc ement : USCS607 1 3
SEMESTER V
THEORY
Course:
USCS5 01 TOPICS (Credits : 03 Lectures/Week:03)
Artificial Intelligence
Objectives:
Artificial Intelligence (AI) and accompanying tools and techniques bring transformational
changes in the world. Machines capability to match, and sometimes even surpass human
capability, make AI a hot topic in Computer Science. This course aims to introduc e the learner to
this interesting area.
Expected Learning Outcomes:
After completion of this course, learner should get a clear understanding of AI and different search
algorithms used for solving problems. The learner should also get acquainted with d ifferent
learning algorithms and models used in machine learning.
Unit I What Is AI: Foundations, History and State of the Art of AI.
Intelligent Agents: Agents and Environments, Nature of Environments,
Structure of Agents.
Problem Solving by searching: Problem -Solving Agents, Example Problems,
Searching for Solutions, Uninformed Search Strategies, Informed (Heuristic)
Search Strategies, Heuristic Functions. 15L
Unit II Learning from Examples: Forms of Learning, Supervised Learning, Learning
Decision Trees, Evaluating and Choosing the Best Hypothesis, Theory of
Learning, Regression and Classification with Linear Models, Artificial Neural
Networks, Nonparametric Models, Support Vector Machines, Ensemble
Learning, Practical Machine Learning 15L
Unit III Learning probabilistic models: Statistical Learning, Learning with Complete
Data, Learning with Hidden Variables: The EM Algorithm. Reinforcement
learning: Passive Reinforcement Learning, Active Reinforcement Learning,
Generalization in Reinforcement Lear ning, Policy Search, Applications of
Reinforcement Learning. 15L
Textbook (s):
1) Artificial Intelligence: A Modern Approach, Stuart Russell and Peter Norvig ,3rd Edition,
Pearson, 2010.
Additional Reference (s):
1) Artificial Intelligence: Foundations of Computational Agents , David L Poole ,Alan K.
Mackworth , 2nd Edition , Cambridge University Press , 2017 .
2) Artificial Intelligence, Kevin Knight and Elaine Rich, 3rd Edition, 2017
3) The Elements of Statistical Learning, Trevor Hastie, Robert Tibs hirani and Jerome Friedman,
Springer , 2013
Course:
USCS 502 TOPICS (Credits : 0 3 Lectures/Week:03)
Linux Server Administration
Objectives:
Demonstrate proficiency with the Linux command line interface, directory & file management
techniques, file system organization, and tools commonly found on most Linux distributions.
Effectively operate a Linux system inside of a network environment to integrate with existing service
solutions. Demonstrate the ability to troubleshoot challenging technical problems typically
encountered when operating and admin istering Linux systems.
Expected Learning Outcomes:
Learner will be able to develop Linux based systems and maintain . Learner will be able to install
appropriate service on Linux server as per requirement . Learner will have proficiency in Linux server
administration .
Unit I Introduction:
Technical Summary of Linux Distributions, Managing Software
Single -Host Administration:
Managing Users and Groups, Booting and shutting down processes, File Systems,
Core System Services, Process of configuring, compiling, Linux Kernel
Networking and Security:
TCP/IP for System Administrators, basic network Configuration, Linux Firewall
(Netfilter), System and network security 15L
Unit II Internet Services:
Domain Name System (DNS), File Transfer Protocol (FTP), Apache web server,
Simple Mail Transfer Protocol (SMTP), Post Office Protocol and Internet Mail
Access Protocol (POP and IMAP), Secure Shell (SSH), Network Authentication,
OpenLDAP Server, Samba and L DAP, Network authentication system
(Kerberos), Domain Name Service (DNS), Security 15L
Unit III Intranet Services:
Network File System (NFS), Samba, Distributed File Systems (DFS), Network
Information Service (NIS), Lightweight Directory Access Protocol (LDAP),
Dynamic Host Configuration Protocol (DHCP), MySQL, LAMP Applications
File Servers, Email Services, Chat Applications, Virtual Private Networking . 15L
Textbook (s):
1) Linux Administration: A Beginner’s Guide, Wale Soyinka, Seventh Edition, McGraw -Hill
Education, 2016
2) Ubuntu Server Guide, Ubuntu Documentation Team, 2016
Additional Reference (s):
1) Mastering Ubuntu Server, Jay LaCroi x, PACKT Publisher, 2016
Course:
USCS5 03 TOPICS (Credits : 0 3 Lectures/Week:03)
Software Testing and Quality Assurance
Objectives :
To provide learner with knowledge in Software Testing techniques. To understand how testing
methods can be used as an effective tools in providing quality assurance concerning for software.
To provide skills to design test case plan for testing software
Expected Learning Outcomes:
Understand various software testing methods and strategies. Understand a variety of software
metrics, and identify defects and managing those defects for improvement in quality for given
software. Design SQA activities, SQA strategy, formal technical review report for software
quality control and assurance.
Unit I Software Testi ng and Introduction to quality : Introduction, Nature of errors,
an example for Testing, Definition of Quality , QA, QC, QM and SQA , Software
Development Life Cycle, Software Quality Factors
Verification and Validation : Definition of V &V , Different types of V & V
Mechanisms, Concepts of Software Reviews, Inspection and Walkthrough
Software Testing Techniques : Testing Fundamentals, Test Case Design, White
Box Testing and its types, Black Box Testing and its types 15L
Unit II Software Testing Strategies : Strategic Approach to Software Testing, Unit
Testing, Integration Testing, Validation Testing, System Testing
Software Metrics : Concept and Developing Metric s, Different types of Metrics,
Complexity metrics
Defect Management : Definition of Defects, Defect Management Process,
Defect Reporting, Metrics Related to Defects, Using Defects for Process
Improvement . 15L
Unit III Software Quality Assurance : Quality Concepts , Quality Movement,
Background I ssues , SQA activities , Software Reviews, Formal Technical
Reviews, Formal approaches to SQA , Statistical Quality Assurance, Software
Reliability, The ISO 900 0 Quality Standard s, , SQA Plan , Six sigma, Informal
Reviews 15L
Quality Improvement : Introduction, Pareto Diagrams, Cause -effect Diagrams,
Scatter Diagrams, Run charts
Quality Costs : Defining Quality Costs, Types of Quality Costs, Quality Cost
Measurement, Utilizing Quality Costs for Decision -Making
Textbook (s):
1. Software Engineering for Students, A Programming Approach, Douglas Bell, 4th
Edition,, Pearson Education, 2005
2. Software Engineering – A Practitioners Approach, Roger S. Pressman, 5th Edition, Tata
McGraw Hill, 2001
3. Quality Management, Donna C. S. Summers, 5th Edition, Prentice -Hall, 2010.
4. Total Quality Management, Dale H. Besterfield, 3rd Edition, Prentice Hall, 2003.
Additional Reference(s) :
1. Software engineering: An Engineering approach , J.F. Peters, W. Pedrycz , John
Wiley,2004
2. Software Testing and Quality Assurance Theory and Practice, Kshirsagar Naik,
Priyadarshi Tripathy , John Wiley & Sons, Inc. , Publication, 2008
3. Software Engineering and Testin g, B. B. Agarwal, S. P. Tayal, M. Gupta, Jones and
Bartlett Publishers, 2010
Course:
USCS5 04 TOPICS (Credits : 03 Lectures/Week:03)
Information and Network Security
Objectives:
To provide students with knowledge of basic concepts of computer security including network
security and cryptography.
Expected Learning Outcomes:
Understand the principles and practices of cryptographic techniques. Understand a variety of
generic security threats and vulnerabilities, and identify & analyze particular security problems
for a given application. Understand various protocols for network security to protect against the
threats in a network
Unit I Introduction: Security Trends, The OSI Security Architecture, Security
Attacks, Security S ervices, Security Mechanisms
Classical Encryption Techniques: Symmetric Cipher Model, Substitution
Techniques, Transposition Techniques, Steganography, Block Cipher
Principles, The Data Encryption Standard, The Strength of DES, AES (round
details not expec ted), Multiple Encryption and Triple DES, Block Cipher
Modes of Operation, Stream Ciphers
Public -Key Cryptography and RSA: Principles of Public -Key
Cryptosystems, The RSA Algorithm 15L
Unit II Key Management: Public -Key Cryptosystems, Key Management,
Diffie -Hellman Key Exchange
Message Authentication and Hash Functions : Authentication Requirements,
Authentication Functions, Message Authentication Codes, Hash Functions,
Security of Hash Functions and Macs, Secure Hash Algorithm, HMAC
Digital Signatures and Authentication: Digital Signatures, Authentication
Protocols, Digital Signature Standard
Authentication Applications: Kerberos, X.509 Authentication, Public -Key
Infrastructure 15L
Unit III Electronic Mail Security: Pretty Good Privacy, S/MIME
IP Security: Overview, Architecture, Authentication Header, Encapsulating
Security Payload, Combining Security Associations, Key Management
Web Security: Web Security Considerations, Secure Socket Layer and
Transport Layer Security, Secure Electronic Transaction
Intrusion: Intruders, Intrusion Techniques, Intrusion Detection
Malicious Software: Viruses and Related Threats, Virus Countermeasures,
DDOS
Firew alls: Firewall Design Principles, Types of Firewalls 15L
Textbook (s):
1) Cryptography and Network Security: Principles and Practice 5th E dition, William
Stallings, Pearson ,2010
Additional Reference (s):
1) Cryptography and Network Security , Atul Kahate, Tata McGraw -Hill, 2013.
2) Cryptography and Network, Behrouz A Fourouzan, Debdeep Mukhopadhyay, 2nd
Edition ,TMH ,2011
Course :
USCS 505 TOPICS (Credits : 03 Lectures/Week: 03)
Architecting of IoT
Objectives:
Discover ing the interconnection and integration of the physical world. Learner should get knowledge
of the architecture of IoT.
Expected Learning Outcomes:
Learners are able to design & develop Io T Devices. They should also be aware of the evolving world of
M2M Communications and IoT analytics .
Unit I IoT-An Architectural Overview : Building architecture , Main design principles
and needed capabilities, An IoT architecture outline, standards considerations.
IoT Architecture -State of the Art : Introduction, State of the art, Reference
Model and architecture, IoT reference Model - IoT Reference Architecture
Introduction, Functional View, Information View, Deployment and Operational
View, Other Relevant architectural views 15L
Unit II IoT Data Link Layer and Network Layer Protocols :
PHY/MAC Layer(3GPP MTC, IEEE 802.11, IEEE 802.15), Wireless
HART,Z -Wave, Bluetooth Low Energy, Zigbee Smart Energy DASH7
Network Layer :IPv4, IPv6, 6LoWPAN, 6TiSCH,ND, DHCP, ICMP, RPL,
CORPL, CARP 15L
Unit III Transport layer protocols :
Transport Layer (TCP, MPTCP, UDP, DCCP, SCTP) -(TLS, DTLS)
Session layer :
Session Layer -HTTP, CoAP, XMPP, AMQP, MQTT
Service layer protocols :
Service Layer -oneM2M, ETSI M2M, OMA, BBF 15L
Textbook (s):
1. From Machine -to-Machine to the Internet of Things: Introducti on to a New Age of
Intelligence , Jan Holler, Vlasios Tsiatsis, Catherine Mulligan, Stefan Avesand, Stamatis
Karnouskos, David Boyle ,1st Edition, Academic Press, 2014.
2. Learning Internet of Things , Peter Waher, PACKT publishing, BIRMINGHAM –
MUMBAI ,2015
Additional References (s):
1. Building the Internet of Things with IPv6 and MIPv6: The Evolv ing World of M2M
Communications , Daniel Minoli, Wiley Publications ,2013
2. Internet of Things (A Hands -onApproach) , Vijay Madisetti and ArshdeepBahga ,1st Edition,
VPT, 2014.
3. http://www.cse.wustl.edu/~jain/cse570 -15/ftp/iot_prot/index.html
Course:
USCS5 06 TOPICS (Credits : 03 Lectures/Week:03)
Web Services
Objectives:
To understand the details of web services technologies like SOAP, WSDL, and UDDI. To learn
how to implement and deploy web service client and server. To understand the design principles
and application of SOAP and REST based web services (JAX -Ws and JAX -RS).To understand
WCF service. To design secure web services and QoS of Web Services
Expected Learning Outcomes:
Emphasis on SOAP based web services and associated standards such as WSDL. Design SOA P
based / RESTful / WCF services Deal with Security and QoS issues of Web Services
Unit I Web services basics :
What Are Web Services? Types of Web Services Distributed computing
infrastructure, overview of XML, SOAP, Building Web Services with
JAX-WS, Registering and Discovering Web Services, Service Oriented
Architecture, Web Services Development Life Cycle, Developing and
consuming simple Web Services across platform 15L
Unit II The REST A rchitectural style :
Introducing HTTP, The core architectural elements of a RESTful system,
Description and discovery of RESTful web services, Java tools and
frameworks for building RESTful web services, JSON message format and
tools and frameworks around JSON, Build RESTful web services with
JAX-RS API s, The Description and Discovery of RESTful Web Services,
Design guidelines for building RESTful web services, Secure RESTful web
services 15L
Unit III Developing Service -Oriented Applications with WCF :
What Is Windows Communication Foundation, Fundamental Windows
Communication Foundation Concepts, Windows Communication Foundation
Architecture, WCF and .NET Framework Client Profile, Basic WCF
Programming, WCF Feature Details . Web Service QoS 15L
Textbook(s):
1) Web Services: Principles and Technolo gy, Michael P. Papazoglou, Pearson Education
Limited, 2008
2) RESTful Java Web Services, Jobinesh Purushothaman, PACKT Publishing, 2nd Edition, 2015
3) Developing Service -Oriented Applications with WCF, Microsoft, 2017
https://docs.microsoft.com/en -us/dotnet/framework/wcf/index
Additional Reference(s):
1) Leonard Richardson and Sam Ruby, RESTful Web Services, O’Reilly, 2007
2) The Java EE 6Tutorial, Oracle, 2013
Course :
USCS5 07 TOPICS (Credits : 03 Lectures/Week: 03)
Game Programming
Objectives :
Learner should get the understanding computer Graphics programming using Directx or Opengl .
Along with the VR and AR they should also aware of GPU, newer technologies and programming
using most important API for windows.
Expected Learning Outcomes:
Learner should study Graphics and gamming concepts with present working style of developers where
everything remains on internet and they need to review it, understand it, be a part of community and
learn.
Unit I
Mathematics for Computer Graphics, DirectX Kickstart:
Cartesian Coordinate system: The Cartesian XY -plane, Function Graphs,
Geometric Shapes, Polygonal Shapes, Areas of Shapes, Theorem of Pythagoras
in 2D, Coordinates, Theorem of Pythagoras in 3D, 3D Poly gons, Euler’s Rule
Vectors: Vector Manipulation, multiplying a Vector by a Scalar, Vector
Addition and Subtraction, Position Vectors, Unit Vectors, Cartesian Vectors,
Vector Multiplication, Scalar Product, Example of the Dot Product, The Dot
Product in Lig hting Calculations, The Dot Product in Back -Face Detection, The
Vector Product, The Right -Hand Rule, deriving a Unit Normal Vector for a
Triangle Areas, Calculating 2D Areas
Transformations: 2D Transformations, Matrices, Homogeneous Coordinates,
3D Transfo rmations, Change of Axes, Direction Cosines, rotating a Point about
an Arbitrary Axis, Transforming Vectors, Determinants, Perspective Projection,
Interpolation
DirectX : Understanding GPU and GPU architectures. How they are different
from CPU Architectures ? Understanding how to solve by GPU? 15L
Unit II DirectX Pipeline and Programming:
Introduction To DirectX 11: COM, Textures and Resources Formats, The
swap chain and Page flipping, Depth Buffering, Texture Resource Views,
Multisampling Theory and MS in Direct3D, Feature Levels
Direct3D 11 Rendering Pipeline: Overview, Input Assembler Stage (IA),
Vertex Shader Stage (VS), The Tessellation Stage (TS), Geometry Shader Stage
(GS), Pixel Shader Stage (PS), Output merger Stage (OM)
Understanding Meshes or Obj ects, Texturing, Lighting, Blending.
Interpolation and Character Animation :
Trigonometry: The Trigonometric Ratios, Inverse Trigonometric Ratios,
Trigonometric Relationships, The Sine Rule, The Cosine Rule, Compound
Angles, Perimeter Relationships
Interpolation : Linear Interpolant, Non -Linear Interpolation, Trigonometric
Interpolation, Cubic Interpolation, Interpolating Vectors, Interpolating
Quaternions
Curves: Circle, Bezier, B -Splines
Analytic Geometry: Review of Geometry, 2D Analytic Geometry, I ntersection
Points, Point in Triangle, and Intersection of circle with straight line. 15L
Unit III Introduction to Rendering Engines: Understanding the current market
Rendering Engines. Understanding AR, VR and MR.Depth Mappers, Mobile
Phones, Smart Glasses, HMD’s
Unity Engine: Multi -platform publishing, VR + AR : Introduction and
working in Unity, 2D, Graphics, Physics, Scripting, Animation, Timeline,
Multiplayer and Networking, UI, Navigation and Pathfinding, XR, Publishing.
Scripting: Scripting Overview, Scripting Tools and Event Overview
XR: VR, AR, MR, Conceptual Differences. SDK, Devices 15L
Text Book(s):
1) Mathe matics for Computer Graphics, John Vince, Springer -Verlag London , 5th Edition,2017
2) Mathematics for 3D Game Programm ing and Computer Graphic, Eric L engyel, Delmar
Cengage Learning , Delmar Cengage Learning,2011
3) Introduction To 3D Game Programming With Directx® 11, Frank D Luna, Mercury Learning
And Information ,2012.
4) https://docs.unity3d.com/Manual/index.html - Free
Additional Reference(s):
1) Computer Graphics , C Version , Donald Hern and Pauline Baker, Pearson Education , 2nd
Edition, 1997
2) HLSL Develop ment Cookbook, Doron Feinstein, P ACKT Publishing ,2013
Suggested List of Practical - SEMESTER V
Course :
USCSP 501 (Credits : 02 Lectures/Week: 06)
Practical of Elective -I
USCS501 : Artificial Intelligence
Practica l shall be implemented in LISP
1. Implement Breadth first search algorithm for Romanian map problem.
2. Implement Iterative deep depth first search for Romanian map problem.
3. Implement A* search algorithm for Romanian map problem.
4. Implement recursive best -first search algorithm for Romanian map problem.
5. Implement decision tree learning algorithm for the restaurant waiting problem.
6. Implement feed forward back propagation neural network learning algorithm for the restaurant
waiting problem.
7. Implement Adaboost ensemble learning algorithm for the restaurant waiting problem.
8. Implement Naive Bayes’ learning algorithm for the restaurant waiting problem.
9. Implement passive reinforcement learning algorithm based on adaptive dynamic programming
(ADP) for the 3 by 4 world problem
10. Implement passive reinforcement learning algorithm based on temporal differences (TD) for 3
by 4 world problem.
USCS502 : Linux Server Administration
- Practical shall be performed using any Linux Server (with 8GB RAM).
- Internet connection will be required so that Linux server (command line mode) can be connected
to Internet .
1. Install DHCP Server in Ubuntu 16.04
2. Initial settings: Add a User, Network Settings, Change to static IP address, Disable IPv6 if not
needed, Configure Services, display the list of services which are running, Stop and turn OFF
auto-start setting for a service if you don’t need it, Sudo Setti ngs
3. Configure NTP Server (NTPd), Install and Configure NTPd, Configure NTP Client (Ubuntu
and Windows)
4. SSH Server : Password Authentication
Configure SSH Server to manage a server from the remote computer, SSH Client : (Ubuntu and
Windows)
5. Install DNS Serv er BIND, Configure DNS server which resolves domain name or IP address,
Install BIND 9, Configure BIND, Limit ranges you allow to access if needed.
6. Configure DHCP Server, Configure DHCP (Dynamic Host Configuration Protocol) Server,
Configure NFS Server to share directories on your Network, Configure NFS Client. (Ubuntu
and Windows Client OS)
7. Configure LDAP Server, Configure LDAP Server in order to share users' accounts in your local
networks, Add LDAP User Accounts in the OpenLDAP Server, Configure LDAP Cli ent in
order to share users' accounts in your local networks. Install phpLDAPadmin to operate LDAP
server via Web browser.
8. Configure NIS Server in order to share users' accounts in your local networks, Configure NIS
Client to bind NIS Server.
9. Install MySQL to configure database server, Install phpMyAdmin to operate MySQL on web
browser from Clients.
10. Install Samba to share folders or files between Windows and Linux.
USCS503 : Software Testing and Quality Assurance
1. Install Selenium IDE; W rite a test suite containing minimum 4 test cases for different formats.
2. Conduct a test suite for a ny two web sites.
3. Install Selenium server (Selenium RC) and demonstrate it using a script in Java /PHP.
4. Write and test a program to login a specific web page.
5. Write and test a program to update 10 student records into table into Excel file
6. Write and test a program to select the number of students who have scored more than 60 in any
one subject (or all subjects) .
7. Write and test a program to provide total number of obje cts present / available on the page .
8. Write and test a program to get the number of items in a list / combo box.
9. Write and test a program to count the number of check boxes on the page checked and
unchecked count .
10. Load Testing using JMeter, Android Applicat ion testing using Appium Tools, Bugzilla Bug
tracking tools.
Course :
USCS P502 (Credits : 02 Lectures/Week: 06)
Practical of Elective -II
USCS504 : Information and Network security
1.Write programs to implement the following Substitution Cipher Techniques:
- Caesar Cipher
- Monoalphabetic Cipher
2 Write programs to implement the following Substitution Cipher Techniques:
- Vernam Cipher
- Playfair Cipher
3 Write programs to implement the following Transposition Cipher Techniques:
- Rail Fence Cipher
- Simple Columnar Technique
4 Write program to encrypt and decrypt strings using
- DES Algorithm
- AES Algorithm
5 Write a program to implement RSA algorithm to perform encryption / decryption of a given
string.
6 Write a program to implement the Diffie -Hellman Key Agreement algorithm to generate
symmetric keys.
7 Write a program to implement the MD5 algorithm compute the message digest.
8 Write a program to calculate HMAC -SHA1 Signature
9 Write a program to implement SSL.
10 Configure Windows Firewall to block:
- A port
- An Program
- A website
USCS505 : Architecting of IoT
1. a) Edit text files with nano and cat editor, Learn sudo privileges and Unix shell
commands such as cd , ls , cat, etc
b) Learn to set dynamic and static IP. Connect to and Ethernet and WiFi network.
Learn to vnc and ssh into a raspberry pi using vnc and putty from a different comput er on the network.
c) Write a basic bash script to open programs in kiosk mode. Learn how to autostart
programs on boot.
2. Run the node red editor and run simple programs and trigger gpios. Use basic nodes
such as inject, debug, gpio
3. Open the python idle editor and run simple Python scripts such as to print Fibonacci
numbers, string functions. Learn how to install modules using Pip and write functions
4. Setup a physical button switch and trigger an led in node red and python w debounce
5. Write simple JavaScript functions in Node -Red simple HTTP server page using node red
6. Setup a TCP server and client on a raspberry pi using Python modules to send
messages and execute shell commands from within python such as starting another
application
7. Trigger a set of led Gpios on the pi via a Python Flask web server
8. Interface the raspberry pi with a 16x2 LCD display and print values.
9. Setup a Mosquitto MQTT server and client and write a Python script to communicate data
between Pi's.
10. Interface with an Accelerometer Gyro Mpu6050 on the i2c bus and send sensor values over the
internet via mqtt.
USCS 506: Web Services
1. Write a program to implement to create a simple web service that converts the temperature
from Fahrenheit to Celsius and vice a versa.
2. Write a program to implement the operation can receive request and will return a response in
two ways. a) One - Way operation b) Request –Response
3. Write a program to implement business UDDI Registry entry.
4. Develop client which consumes web services developed in different platform.
5. Write a JAX -WS web service to perform the following ope rations. Define a Servlet / JSP that
consumes the web service.
6. Define a web service method that returns the contents of a database in a JSON string. The
contents should be displayed in a tabular format.
7. Define a RESTful web service that accepts the details to be stored in a database and performs
CRUD operation.
8. Implement a typical service and a typical client using WCF.
9. Use WCF to create a basic ASP.NET Asynchronous JavaScript and XML (AJAX) service.
10. Demonstrates using the binding attribute of an endpoint e lement in WCF.
Course :
USCSP 503 (Credits : 01 Lectures/Week: 0 3)
Project Implementation
Please Refer to Project Implementation Guidelines
Course :
USCSP504 (Credits : 01 Lectures/Week: 03 )
Practical of Skill Enhancement
USCS507 : Game Programming
1. Setup DirectX 11, Window Framework and Initialize Direct3D Device
2. Buffers, Shaders and HLSL (Draw a triangle using Direct3D 11)
3. Texturing (Texture the Triangle using Direct 3D 11)
4. Lightning (Programmable Diffuse Lightning using Direct3D 11)
5. Specular Lightning (Programmable Spot Lightning using Direct3D 11)
6. Loading models into DirectX 11 and rendering.
Perform following Practical using online content from the Unity Tutorials Web --sites:
https://unity3d.com/learn/tutorials/s/interactive -tutorials
7. https://unity3d.com/learn/tutorials/s/2d -ufo-tutorial
8. https://unity3d.com/learn/tutorials/s/space -shooter -tutorial
9. https://unity3d.com/learn/tutorials/s/roll -ball-tutorial
10. https://unity3d.co m/learn/tutorials/topics/vr/introduction?playlist=22946
SEMESTER VI
THEORY
Course:
USCS601 TOPICS (Credits : 03 Lectures/Week: 03 )
Wireless Sensor Networks and Mobile Communication
Objectives:
In this era of wireless and adhoc network, connecting different wireless devices and understanding
their compatibility is very important. Information is gathered in many different ways from these
devices. Learner should be able to conceptualize and underst and the framework. On completion, will
be able to have a firm grip over this very important segment of wireless network.
Expected Learning Outcomes:
After completion of this course, learner should be able to list various applications of wireless sensor
networks, describe the concepts, protocols, design, implementation and use of wireless sensor
networks. Also implement and evaluate new ideas for solving wireless sensor network design issues.
Unit I Introduction: Introduction to Sensor Networks, unique constraints and
challenges.
Advantage of Sensor Networks, Applications of Sensor Networks,
Mobile Adhoc NETworks (MANETs) and Wireless Sensor Networks,
Enabling technologies for Wireless Sensor Networks.
Sensor Node Hardware and Network Architecture: Single -node
architecture, Hardware components & design constraints, Operating
systems and execution environments, int roduction to TinyOS and nesC.
Network architecture, Optimization goals and figures of merit, Design
principles for WSNs, Service interfaces of WSNs, Gateway concepts. 15L
Unit II Medium Access Control Protocols : Fundamentals of MAC Protocols,
MAC Protocols for WSNs, Sensor -MAC Case Study.
Routing Protocols : Data Dissemination and Gathering, Routing
Challenges and Design Issues in Wireless
Sensor Networks, Routing Strategies in Wireless Sensor Networks.
Transport Control Protocols : Traditional Transport Control Protocols, 15L
Transport Protocol Design Issues, Examples of Existing Transport
Control Protocols, Performance of Transport Control Protocols.
Unit III Introduction, Wireless Transmission and Medium Access Control:
Applications, A short history of wireless communication.
Wireless Transmission: Frequency for radio transmission, Signals,
Antennas, Signal propagation, Multiplexing, Modulation, Spread
spectrum, Cellular systems.
Telecommunication, Satellite and Broadcast Systems: GSM: Mobile
services, System architecture, Radio interface, Protocols, Localization
And Calling, Handover, security, New data services; DECT: System
architecture, Protocol architecture; ETRA, UMTS and IMT - 2000.
Satellite Systems: History, Applications, Basics: GEO, LEO, MEO;
Routing, Localization, Handover. 15L
Textbook(s):
1) Protocols and Architectu res for Wireless Sensor Network , Holger Kerl, Andreas Willig,
John Wiley and Sons , 2005
2) Wireless Sensor Networks Technology, Protocols, and Applications ,Kazem Sohraby ,
Daniel Minoli and TaiebZnati, John Wiley & Sons, 2007
3) Mobile communications , Jochen Schiller,2nd Edition, Addison wisely , Pearson
Education ,2012
Additional Reference(s):
1) Fundamentals of Wireless Senso r Networks, Theory and Practice , Waltenegus Dargie,
Christian Poellabauer , Wiley Series on wireless Communication and Mobile Computing,
2011
2) Networking Wireless Sensors , Bhaskar Krishnamachari , Cambridge University Press, 2005
Course :
USCS6 02 TOPICS (Credits : 03 Lectures/Week: 03)
Cloud Computing
Objectives :
To provide learners with the comprehensive and in -depth knowledge of Cloud Computing concepts,
technologies, architecture, implantations and applications . To expose the learners to frontier areas of
Cloud Computing, while providing sufficient foundations to enable further study and research.
Expected Learning Outcomes:
After suc cessfully co mpletion of this course, learner should be able to articulate the main concepts, key
technologies, strengths, and limitations of cloud computing and the possible applications for
state-of-the-art cloud computing using open source technology . Learner should be able to identify the
architecture and infrastructure of cloud computing, including SaaS, PaaS, IaaS, public cloud, private
cloud, hybrid cloud, etc. They should explain the core issues of cloud computing such as security,
privacy, and int eroperability.
Unit I Introduction to Cloud Computing, Characteristics and benefits of Cloud
Computing, Basic concepts of Distributed Systems, Web 2.0, Service -Oriented
Computing, Utility -Oriented Computing. Elements of Parallel Computing.
Elements of Distributed Computing. Tec hnologies for Distributed Computing.
Cloud Computing Architecture. The cloud reference model. Infrastructure as a
service. Platform as a service. Software as a service. Types of clouds. 15L
Unit II Characteristics of Virtualized Environments. Taxonomy of Virtualization
Techniques. Virtualization and Cloud Computing. Pros and Cons of
Virtualization. Virtualization using KVM, Creating virtual machines, oVirt -
management tool for virtualization environment. Open challenges of Cloud
Computing 15L
Unit III Introduction to OpenStack, OpenStack test -drive, Basic OpenStack operations,
OpenStack CLI and APIs, Tenant model operations, Quotas, Private cloud
building blocks, Controller deployment, Networking deployment, Block Storage
deployment, Compute deployment, d eploying and utilizing OpenStack in
production environments, Building a production environment, Application
orchestration using OpenStack Heat 15L
Textbook (s):
1) Mastering Cloud Computing, Rajkumar Buyya, Christi an Vecchiola, S Thamarai Selvi, Tata
McGraw Hill Education Private Limited, 2013
2) OpenStack in Action, V. K. CODY BUMGARDNER, Manning Publications Co, 2016
Additional Reference (s):
1) OpenStack Essentials, Dan Radez, PACKT Publishing, 2015
2) OpenStack Operations Guide, Tom Fifield, Diane Fleming, Anne Gentle, Lorin Hochstein,
Jonathan Proulx, Everett Toews, and Joe Topjian, O'Reilly Media, Inc., 2014
3) https://www.openstack.org
Course :
USCS6 03 TOPICS (Credits : 03 Lectures/Week:0 3)
Cyber Forensic s
Objectives :
To understand the procedures for identification, preservation, and extraction of electronic evidence,
auditing and investigation of network and host system intrusions, analysis and documentation of
information gathered
Expected Learning Outcome s :
The student will be able to p lan and prepare for all stages of an investigation - detection, initial
response and management interaction , investigate various media to collect evidence, report them in a
way that would be acceptable in the court of law.
Unit I
Computer Forensics :
Introduction to Computer Forensics and standard procedure, Incident
Verification and System Identification ,Recovery of Erased and damaged data,
Disk Imaging and Preservation, Data Encryption and Compression, Automated
Search Technique s, Forensics Software
Network Forensic :
Introduction to Network Forensics and tracking network traffic, Reviewing
Network Logs, Network Forensics Tools, Performing Live Acquisitions, Order
of Volatility, Standard Procedure
Cell Phone and Mobile Device Fo rensics: Overview, Acquisition Procedures
for Cell Phones and Mobile Devices 15L
Unit II Internet Forensic :
Introduction to Internet Forensics, World Wide Web Threats, Hacking and
Illegal access, Obscene and Incident transmission, Domain Name Ownership
Investigation, Reconstructing past internet activities and events
E-mail Forensics : e-mail analysis, e -mail headers and spoofing, Laws against
e-mail Crime, Messenger Forensics: Yahoo Messenger
Social Media Forensics: Social Media Investigations
Browser Forensics: Cookie Storage and Analysis, Analyzing Cache and
temporary internet files, Web browsing activity reconstruction 15L
Unit III Investigation, Evidence presentation and Legal aspects of Digital Forensics:
Authorization to collect the evidence , Acquisition of Evidence, Authentication
of the evidence, Analysis of the evidence, Repo rting on the findings, Testimony
Introduction to Legal aspects of Digital Forensics: Laws & regulations,
Information Technology Act, Giving Evidence in court, Case Study – Cyber
Crime cases, Case Study – Cyber Crime cases 15L
Textbook (s):
1. Guide to computer forensics and investigations, Bill Nelson, Amelia Philips and Christopher
Steuart, course technology,5th Edition ,2015
Additional Reference (s):
2. Incident Response and computer forensics, Kevin Mandia, Chris Prosise, Tata
McGrawHill ,2nd Edition,2003
Course:
USCS6 04 TOPICS (Credits : 03 Lectures/Week: 03)
Information Retrieval
Objectives:
To provide an overview of the important issues in classical and web information retrieval. The focus
is to give an up -to- date treatment of all aspects of the design and implementation of systems for
gathering, indexing, and searching documents and of methods for evaluating systems.
Expected Learning Outcomes:
After completion of this course, learner should get an understanding of the fi eld of information
retrieval and its relationship to search engines. It will give the learner an understanding to apply
information retrieval models.
Unit I Introduction to Information Retrieval: Introduction, History of IR,
Components of IR, and Issues related to IR, Boolean retrieval,
Dictionaries and tolerant retrieval. 15L
Unit II Link Analysis and Specialized Search: Link Analysis, hubs and
authorities, Page Rank and HITS algorithms, Similarity, Hadoop & Map
Reduce, Evaluation, Personalized searc h, Collaborative filtering and
content -based recommendation of documents and products, handling
“invisible” Web, Snippet generation, Summarization, Question
Answering, Cross - Lingual Retrieval. 15L
Unit III Web Search Engine: Web search overview, web structure, the user, paid
placement, search engine optimization/spam, Web size measurement,
search engine optimization/spam, Web Search Architectures.
XML retrieval: Basic XML concepts, Challenges in XML retrieval, A
vector space model for XML retrieval, E valuation of XML retrieval,
Text-centric versus data -centric XML retrieval. 15L
Text book (s):
1) Introduction to Information Retrieval , C. Manning, P. Raghavan, and H. Schütze ,
Cambridge University Press, 2008
2) Modern Information Retrieval: The Concepts and Technology behind Search , Ricardo Baeza
-Yates and Berthier Ribeiro – Neto, 2nd Edition , ACM Press Books 2011.
3) Search Engines: Information Retrieval in Practice, Bruce Croft, Dona ld Metzler and Trevor
Strohman, 1st Edition, Pearson, 2009 .
Additional Reference (s):
1) Information Retrieval Implementing and Evaluating Search Engines, Stefan Büttcher,
Charles L. A . Clarke and Gordon V. Cormack, The MIT Press; Reprint edition (February 12,
2016)
Course :
USCS6 05 TOPICS (Credits : 03 Lectures/Week: 03)
Digital Image Processing
Objectives:
To study two -dimensional Signals and Systems . To u nderstand image fundamentals and transforms
necessary for image processing. To study the image enhancement techniques in spatial and frequency
domain . To study image segmentation and image compression techniques.
Expected Learning Outcome s:
Learner should r eview the fundamental concepts of a d igital image processing system. Analyze the
images in the frequency d omain using various transforms. Evaluate the techniques for image
enhancement and image segmentation . Apply various compression techniques. They will be familiar
with basic image processing techniques for solving real problems.
Unit I Introduction to Image -processing System : Introduction, Image Sampling,
Quantization, Resolution, Human Visual Systems, Elements of an
Image -processing System, Applications of Digital Image Processing
2D Signals and Systems : 2D signals, separable sequence, periodic sequence,
2D systems, classification of 2D systems, 2D Digita l filter
Convolution and Correlation : 2D Convolution through graphical method,
Convolution through 2D Z —transform, 2D Convolution through matrix
analysis, Circular Convolution, Applications of Circular Convolution, 2D
Correlation
Image Transforms : Need f or transform, image transforms, Fourier transform,
2D Discrete Fourier Transform, Properties of 2D DFT, Importance of Phase,
Walsh transform, Hadamard transform, Haar transform, Slant transform,
Discrete Cosine transform, KL transform 15L
Unit II Image Enhancement :Image Enhancement in spatial domain, Enhancement
trough Point operations, Histogram manipulation, Linear and nonlinear Gray
Level Transformation, local or neighborhood operation, Median Filter, Spatial
domain High pass filtering, Bit -plane sli cing, Image Enhancement in frequency
domain, Homomorphic filter, Zooming operation, Image Arithmetic 15L
Binary Image processing :Mathematical morphology, Structuring elements,
Morphological image processing, Logical operations, Morphological
operations, Dilat ion and Erosion, Distance Transform
Colour Image processing :Colour images, Colour Model, Colour image
quantization, Histogram of a colour image
Unit III Image Segmentation : Image segmentation techniques, Region approach,
Clustering techniques, Thresholding, Edge -based segmentation, Edge detection,
Edge Linking, Hough Transform
Image Compression : Need for image compression, Redundancy in images,
Image -compression scheme, Fundamentals of Information Theory, Run -length
coding, Shannon -Fano coding, Huffman Coding, Arithmetic Coding,
Transform -based compression, Image -compression standard 15L
Textbook (s):
1) Digital Image Processing, S Jayarama n, S Esakkirajan, T Veerakumar, Tata McGra w-Hill
Education Pvt. Ltd., 2009
Additional Reference (s):
1) Digital Image Processing 3rd Edition, Rafael C Gonzalez, Richard E Woods, Pearson, 2008
2) Scilab Textbook Companion for Digital Image Processing, S. Jayaraman, S. Esakkirajan And
T. Veerakumar, 2016 (https://scilab.in/textbook_companion/generate_book/125)
Course :
USCS6 06 TOPICS (Credits : 03 Lectures/Week: 03)
Data Science
Objectives :
Understanding basic data science concepts. Learning to detect and diagnose common data issues,
such as missing values, special values, outliers, inconsistencies, and localization . Making aware of
how to address advanced statistical situations, Modeling and Machine Learning .
Expected Learning Outcomes:
After completion of this course, the students should be able to understand & comprehend the
problem; and should be able to define sui table statistical method to be adopted.
Unit I Introduction to Data Science: What is Data? Different kinds of data, 15L
Introduction to hi gh level programming language + Integrated Development
Environment (IDE), Exploratory Data Analysis (EDA) + Data Visualization,
Different types of data sources,
Data Management : Data Collection, Data cleaning/e xtraction, Data analysis &
Modeling
Unit II Data Curation : Query langua ges and Operations to specify and transform data,
Structured/schema based systems as users and acquirers of data
Semi -structured systems as users and acquirers of data, Unstructured systems in
the acquisition and structuring of data, Security and ethical c onsiderations in
relation to authenticating and authorizing access to data on remote systems,
Software development tools, Large scale data syst ems, Amazon Web Services
(AWS) 15L
Unit III Statistical Modelling and Machine Learning:
Introduction to model selection: Regularization, bias/variance tradeoff e.g.
parsimony, AIC, BIC, Cross validation, Ridge regressions and penalized
regression e.g. LASSO
Data transformations : Dimension reduction, Feature extraction, Smoothing
and aggregating
Supervised Learning : Regression, linear models, Regression trees, Time -series
Analysis, Forecasting, Classification: classification trees, Logistic regression,
separating hyperplanes, k -NN
Unsupervised Learning : Principal Components Analysis (PCA), k -means
clustering, Hierar chical clustering, Ensemble methods 15L
Textbook (s):
1) Doing Data Science, Rachel Schutt and Cathy O’Neil, O’Reilly,2013
2) Mastering Machine Learning with R, Cory Lesmeister, PACKT Publication,2015
Additional Reference (s):
1) Hands -On Programming with R, Garrett Grolemund,1st Edition, 2014
2) An Introduction to Statistical Learning, James, G., Witten, D., Hastie, T., Tibshirani,
R.,Springer,2015
Course :
USCS6 07 TOPICS (Credits : 02 Lectures/Week: 03)
Ethical Hacking
Objectives:
To understand the ethics , legality, methodologies and techniques of hacking .
Expected Learning Outcomes:
Learner will know to identify security vulnerabilities and weaknesses in the target applications.
They will also know to test and expl oit systems using various tools and understand the impact of
hacking in real time machines.
Unit I Information Security : Attacks and Vulnerabilities
Introduction to information security : Asset, Access Control, CIA,
Authentication, Authorization, Risk, Threat, Vulnerability, Attack, Attack
Surface, Malware, Security -Functionality -Ease of Use Triangle
Types of malware :Worms, viruses, Trojans, Spyware, Rootkits
Types of vulnerabilities : OWASP Top 10 : cross -site scripting (XSS), cross
site request forgery (CSRF/XSRF), SQL injection, input parameter
manipulation, broken authentication, sensitive information disclosure, XML
External Entities, Broken access control, Security Misconfiguratio n, Using
components with known vulnerabilities, Insufficient Logging and monitoring,
OWASP Mobile Top 10, CVE Database
Types of attacks and their common prevention mechanisms : Keystroke
Logging, Denial of Service (DoS /DDoS), Waterhole attack, brute forc e,
phishing and fake WAP, Eavesdropping, Man -in-the-middle, Session Hijacking,
Clickjacking, Cookie Theft, URL Obfuscation, buffer overflow, DNS poisoning,
ARP poisoning, Identity Theft, IoT Attacks, BOTs and BOTNETs
Case -studies : Recent attacks – Yahoo, Adult Friend Finder, eBay, Equifax,
WannaCry, Target Stores, Uber, JP Morgan Chase, Bad Rabbit 15L
Unit II Ethical Hacking – I (Introduction and pre -attack)
Introduction : Black Hat vs. Gray Hat vs. White Hat (Ethical) hacking, Why is
Ethical hacking needed?, How is Ethical hacking different from security
auditing and digital forensics?, Signing NDA, Compliance and Regulatory 15L
concerns, Black box vs. White box vs. Black box, Vulnerability assessment and
Penetration Testing .
Approach : Planning - Threat Modeling, set up security verification standards,
Set up security testing plan – When, which systems/apps, understanding
functionality, black/gray/white, authenticated vs. unauthenticated, internal vs.
external PT , Information gathering, Perform Manual an d automated (Tools:
WebInspect/Qualys, Nessus, Proxies, Metasploit) VA and PT, How
WebInspect/Qualys tools work: Crawling/Spidering, requests forging, pattern
matching to known vulnerability database and Analyzing results, Preparing
report, Fixing security gaps following the report
Enterprise strategy : Repeated PT, approval by security testing team ,
Continuous Application Security Testing ,
Phases: Reconnaissance/foot -printing/Enumeration , Phases : Scanning, Sniffing
Unit III Ethical Hacking : Enterprise Security
Phases : Gaining and Maintaining Access : Systems hacking – Windows and
Linux – Metasploit and Kali Linux, Keylogging, Buffer Overflows, Privilege
Escalation , Network hacking - ARP Poisoning, Password Cracking, WEP
Vulnerabilities, MAC Spoofing, MAC Flooding, IPSpoofing, SYN Flooding,
Smurf attack , Applications hacking : SMTP/Email -based attacks, VOIP
vulnerabilities, Directory traversal, Input Manipulation, Bru te force attack,
Unsecured login mechanisms, SQL injection, XSS, Mobile apps security ,
Malware analysis : Netcat Trojan, wrapping definition, reverse engineering
Phases : Covering your tracks : Steganography, Event Logs alteration
Additional Security Mecha nisms : IDS/IPS, Honeypots and evasion
techniques, Secure Code Reviews (Fortify tool, OWASP Secure Coding
Guidelines) 15L
Textbook (s):
1) Certifi ed Ethical Hacker Study Guide v9 , Sean -Philip Oriyano, Sybex; Study Guide
Edition,2016
2) CEH official Cert ified Ethical Hacking Review Guide, Wiley India Edition , 2007
Additional Reference (s):
1) Certified Ethical Hacker: Michael Gregg, Pearson Education ,1st Edition, 2013
2) Certified E thical Hacker: Matt Walker, TMH,2011
3) http://www.pentest -standard.org/index.php/PTES_Technical_Guidelines
4) https://www.owasp.org/index.php/Category:OWASP_Top_Ten_2017_Project
5) https://www.owasp.org/index.php/Mobile_Top_10_2016 -Top_10
6) https://www.owasp.org/index.php/OWASP_Testing_Guide_v4_Tabl e_of_Contents
7) https://www.owasp.org/index.php/OWASP_Secure_Coding_Practices_ -_Quick_Reference_
Guide
8) https://cve.mitre.org/
9) https://access.redhat.com/blogs/766093/posts/2914051
10) http://resources.infosecinstitute.com/applications -threat -modeling/#gref
11) http://www.vulnerabilityassessment.co.uk/Penetration%20Test.html
Suggeste d List of Practical – SEMESTER VI
Course :
USCSP 601 (Credits : 02 Lectures/Week:06 )
Practical of Elective -I
USCS6 01: Wireless Sensor Networks and Mobile Communication
Practical experiments require software tools like INET Framework for OMNeT++, NetSim ,
TOSSIM, Cisco packet tracer 6.0 and higher version.
1. Understanding the Sensor Node Hardware. (For Eg. Sensors, Nodes(Sensor mote), Base Station,
Graphical User Interface.)
2. Exploring and understanding TinyOS computational concepts: - Events, Commands and Task.
- nesC model
- nesC Components
3. Understanding TOSSIM for
- Mote -mote radio communication
- Mote -PC se rial communication
4. Create and simulate a simple adhoc network
5. Understanding, Reading and Analyzing Routing Table of a network.
6. Create a basic MANET implementation simulation for Packet animation and Packet Trace.
7. Implement a Wireless sensor network simulation.
8. Create MAC protocol simulation implementation for wireless sensor Network.
9. Simulate Mobile Adhoc Network with Directional Antenna
10. Create a mobile network using Cell Tower, Central Office Server, Web browser and Web Server.
Simulate connection b etween them.
USCS6 02: Cloud Computing
1. Study and implementation of Infrastructure as a Service.
2. Installation and Configuration of virtualization using KVM.
3. Study and implementation of Infrastructure as a Service
4. Study and implementation of Storage as a Service
5. Study and implementation of identity management
6. Study Cloud Security management
7. Write a program for web feed.
8. Study and implementation of Single -Sing-On.
9. User Management in Cloud.
10. Case study on Amazon EC2/Microsoft Azure/Google Cloud Platform
USCS6 03: Cyber Forensic s
1. Creating a Forensic Image using FTK Imager/Encase Imager :
- Creating Forensic Image
- Check Integrity of Data
- Analyze Forensic Image
2. Data Acquisition :
- Perform data acquisition using:
- USB Write Blocker + Encase Imager
- SATA Write Blocker + Encase Imager
- Falcon Imaging Device
3. Forensics Case Study :
- Solve the Case study (image file) provide in lab using Encase Investigator or Autopsy
4. Capturing and analyzing network packets using Wireshark (Fundamentals) :
- Identification the live network
- Capture Packets
- Analyze the captured packets
5. Analyze the packets provided in lab and solve the questions using Wireshark :
- What web server software is used by www.snopes.com ?
- About what cell phone problem is the client concerned?
- According to Zillow, what instrument will Ryan learn to play?
- How many web servers are running Apache?
- What hosts (IP addresses) think that jokes are more entertaining when they are e xplained?
6. Using Sysinternals tools for Network Tracking and Process Monitoring :
- Check Sysinternals tools
- Monitor Live Processes
- Capture RAM
- Capture TCP/UDP packets
- Monitor Hard Disk
- Monitor Virtual Memory
- Monitor Cache Memory
7. Recovering and Inspecting deleted files
- Check for Deleted Files
- Recover the Deleted Files
- Analyzing and Inspecting the recovered files
Perform this using recovery option in ENCASE and a lso Perform manually through command
line
8. Acquisition of Cell phones and Mobile devices
9. Email Fo rensics
- Mail Service Providers
- Email protocols
- Recovering emails
- Analyzing email header
10. Web Browser Forensics
- Web Browser working
- Forensics activities on browser
- Cache / Cookies analysis
- Last Internet activity
Course :
USCSP 602 (Credits : 02 Lectures/Week:06 )
Practical of Elective -II
USCS604 : Information R etrieval
Practical may be done using software/tools like Python / Java / Hadoop
1. Write a program to demonstrate bitwise operation.
2. Implement Page Rank Algorithm.
3. Implement Dynamic programming algorithm for computing the edit distance between
strings s1 and s2. (Hint. Levenshtein Distance)
4. Write a program to Compute Similarity between two text documents.
5. Write a map -reduce program to count the number of occurrences of each alphabetic
character in the given dataset. The count for each letter should be case -insensitive (i.e.,
include both upper -case and lower -case versions of the letter; Ignore non -alphabetic
characters).
6. Implement a basic IR system using Lucene.
7. Write a program for Pre -processing of a Text Document: stop word removal.
8. Write a program for mining Twitter to identify tweets for a specific period and identify
trends and named entities.
9. Write a program to implement simple web crawler.
10. Write a program to parse XML text, generate Web graph and compute topic specific page
rank.
USCS605 : Digital Image Processing
Practical need to be performed using Scilab under Linux or Windows
1. 2D Linear Convolution, Circular Convolution between two 2D matrices
2. Circular Convolution expressed as linear convolution plus alias
3. Linear Cross correlation of a 2D matrix, Circular correlation between two signals and Linear auto
correlation of a 2D matrix, Linear Cross correlation of a 2D matrix
4. DFT of 4x4 gray scale image
5. Compute discrete cosine transform, Program to perform KL transform for the given 2D matrix
6. Brightness enhancement of an image, Contrast Manipulation, image negative
7. Perform threshold operation, perform gray level slicing without background
8. Image Segmentation
9. Image Compression
10. Binary Image Processing and Colour Image processing
USCS606:Data Science
Practical shall be performed using R
1. Practical of Data collection, Data curation and management for Unstructured data (NoSQL)
2. Practical of Data collection, Data curation and management for Large -scale Data system (such as
MongoDB)
3. Practical of Principal Component Analysis
4. Practical of Clustering
5. Practical of Time -series forecasting
6. Practical of Simple/Multiple Linear Regression
7. Practical of Logistics Regression
8. Practical of Hypothesis testing
9. Practical of Analysis of Variance
10. Practical of Decision Tree
Course :
USCSP 603 (Credits : 01 Lectures/Week: 03 )
Project Implementation
Please Refer to Project Implementation Guidelines
Course :
USCSP 604 (Credits : 01 Lectures/Week: 0 3)
Practical of Skill Enhancement
USCS6 07 : Ethical Hacking
1. Use Google and Whois for Reconnaissance
2. a) Use CrypTool to encrypt and decrypt passwords using RC4 algorithm
b) Use Cain and Abel for cracking Windows account password using Dictionary attack and to
decode wireless network passwords
3. a) Run and analyze the output of following commands in Linux – ifconfig, ping, netstat,
traceroute
b) Perform ARP Poisoning in Windows
4. Use NMap scanner to perform port scanning of various forms – ACK, SYN, FIN, NULL, XMAS
5. a) Use Wireshark (Sniffer) to capture n etwork traffic and analyze
b) Use Nemesy to launch DoS attack
6. Simulate persistent cross -site scripting attack
7. Session impersonation using Firefox and Tamper Data add -on
8. Perform SQL injection attack
9. Create a simple keylogger using python
10. Using Metasploit to exploit (Kali Linux)
Project Implementation Guidelines
1. A learner is expected to carry out two different projects: one in Semester V and another in
Semester VI.
2. A learner can choose any topic which is covered in Semester I - semester VI or any other
topic with the prior approval from head of the department/ project in charge.
3. The Project has to be performed individually.
4. A learner is expected to devote around three months of efforts in the project.
5. The project can be application oriented/web -based/databas e/research based.
6. It has to be an implemented work ; just theoretical study will not be acceptable.
7. A learner can choose any programming language, computational techn iques and tools
which have been covered during BSc course or any other with the prior permission of
head of the department/ project guide .
8. A project guide should be assigned to a learner . He/she will assign a schedule for the
project and hand it over to a learner . The guide should oversee the project progress on a
weekly basis by considering the workload of 3 lectures as assigned.
9. The quality of the project will be evaluated based on the novelty of the topic, scope of the
work, relevance to the computer sc ience, adoption of emerging techniques/technologies
and its real -world application.
10. A learner has to maintain a project report with the following subsections
a) Title Page
b) Certificate
A certificate should contain the following information –
- The fact that the student has successfully completed the project as per the syllabus
and that it forms a part of the requirements for completing the BSc degree in
computer science of University of Mumbai.
- The name of the student and the project guide
- The academic year in wh ich the project is done
- Date of submission,
- Signature of the project guide and the head of the department with date along with
the department stamp,
- Space for signature of the university examiner and date on which the project is
evaluated.
c) Self-attested co py of Plagiarism Report from any open source tool.
d) Index Page detailing description of the following with their subsections:
- Title: A suitable title giving the idea about what work is proposed.
- Introduction: An introduction to the topic giving proper back ground of the topic.
- Requirement Specification: Specify Software/hardware/data requirements.
- System Design details : Methodology/Architecture/UML/DFD/Algorithms/protocols etc.
used(whichever is applicable)
- System Implementation: Code implementation
- Resul ts: Test Cases/Tables/Figures/Graphs/Screen shots/Reports etc.
- Conclusion and Future Scope: Specify the Final conclusion and future scope
- References: Books, web links, research articles, etc.
11. The size of the project report shall be around twenty to twenty five pages, excluding the
code.
12. The Project report should be submitted in a spiral bound form
13. The Project should be certified by the concern ed Project guide and H ead of the
department.
14. A learner has to make a presentation of working pro ject and will b e evaluated as per the
Project evaluation scheme
Scheme of Examination
1. Theory:
I. Internal 25 Marks :
a) Test – 20 Marks
20 m arks Test – Duration 40 mins
It will be conducted either using any open sou rce learning management system like Moodle
(Modul ar object-oriented dynamic learning environment)
OR
A test based on an equivalent online course on the contents of the concerned course (subject)
offered by or build using MOOC (Massive Open Online Course) platform.
b) 5 Marks – Active participation in routine class inst ructional deliveries
Overall conduct as a responsible student, m anners, skill in a rticulation,
leadership qu alities demonst rated through organizing co-curricular
activiti es, etc.
II. External 75 Marks as per University Guidelines
11. Practical and Project Examination :
There will be separate Practical examination for Elective -I, II, Skill enhansement and project of these
Elective -I 100, Elective -II: 100 and Skill Enhansement : 50 and Project Impleme ntation : 50.
In the Practical E xamination of Elective -I and II, the student has to perform practical on ea ch of the
subjects chosen. The Marking S cheme for each of the Elective is given below:
Subject
Code Experiment -I Experiment -II Total
Marks
Elective -I USCSP501 /
USCSP601 Experiment -40+J ournal -5
+viva -5
Total:50 M Experiment -40+J ournal -5+viva -
5
Total:50 M 100 M
Elective -II USCSP502 /
USCSP602 Experiment -40+J ournal -5
+viva -5
Total:50 M Experiment -40+J ournal -5+viva -
5
Total:50 M 100 M
Project
Implement
ation USCSP503/
USCSP603 **Project Evaluation Scheme 50M
Skill
Enhanc em
ent USCSP504/
USCSP604 Experiment -40+Journal:5+viva -5
Total -50M 50M
Total Marks 300M
(Certified Journal is compulsory for appearing at the time of P ractical Ex amination )
**Project Evaluation Scheme :
Presentation Working of the
Project Quality of the
Project Viva Documentation
10Marks 10 Marks 10 Marks 10 Marks 10Marks
(Certified Project Document is compulsory for appearing at the time of P roject Presentation)
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