nirma university · enclosure-xiv w.e.f. academic year 2020-21 onwards nirma university institute...

Enclosure-XIV

w.e.f. Academic Year 2020-21 onwards

NIRMA UNIVERSITY

Institute of Technology

Master of Computer Application

Semester-IV

L T P C

3 0 2 4

Course Code 3CA4D301

Course Title Artificial Intelligence

Course Outcomes: At the end of the course, students will be able to -

1. identify the major areas and challenges of artificial intelligence.

2. analyse various search algorithms to solve problems.

3. apply various knowledge representation and reasoning techniques to model problems of the

artificial domain.

4. develop an expert system for various domains.

Syllabus: Teaching

hours: Unit I Introduction : Man vs Computers, AI techniques to help computers to be smarter,

languages of AI, characteristic of AI computing, applications of AI, problem solving by intelligent computers, major components of intelligent system

5

Unit II State Space Search: State space representation, defining the Problems as a State Space

Search, Production systems, Problem Characteristics, Algorithms of problem solving,

Issues involved in problem representation, Types of production system, needs of

heuristic search,

7

Unit III Search and Control Strategies: Uninformed (Blind) and informed search, depth first search, breadth first search, heuristic search techniques: generate-and-test, hill climbing,

best-first search, A*, AO*, problem reduction, constraint satisfaction, means-ends

analysis.

14

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Unit IV Knowledge Representation: Knowledge, representing knowledge, categories of

knowledge representation schemes, logic, reasoning in propositional logic, first order

logic, procedural representation, semantic nets, structured representation

7

Unit V Reasoning under uncertainty: Introduction to reasoning, reasoning with uncertain

knowledge, non-monotonic reasoning, probabilistic reasoning, Bayesian network,

Dampster-Shafer theory, fuzzy reasoning

6

Unit VI Expert Systems: Architecture of an expert system, features of an expert system, actors

of an expert system, examples of an expert system, applications of an expert system, limitations of expert system, limitations of expert system, hybrid AI, intelligent systems.

6

Self-Study: To be decided by the course coordinator at the beginning of the semester, which will be a blend of one

or more of the e-Learning Resources, Video Lectures, Online courses, tools, research material, web links etc.

Laboratory Work: The Practical work will be based on the topics covered in the syllabus. Minimum 5 experiments are to be carried out.

Suggested Readings^: 1. Elaine Rich and Kevin Knight, Artificial Intelligence, Tata McGraw-Hill.

2. Russell and Norving, Artificial Intelligence A Modern Approach, Pearson. 3. D.W. Patterson, Artificial Intelligence And Expert Systems, Prentice Hall of India.

4. D.W. Rolston, Artificial Intelligence And Expert System, Development, McGraw-Hill

International Edition. 5. Deepak Khemani, A First Course in Artificial Intelligence, McGraw-Hill

6. Carl Townsend, Introduction to Prolog Programming, BPB publications.

7. Ivan Bratko, PROLOG Programming For Artificial Intelligence, Addison-Wesley.

L = Lecture, T = Tutorial, P = Practical, C = Credit___________________________________________

^ this is not an exhaustive list

Enclosure-XIV


NIRMA UNIVERSITY



Semester-IV

L T P C

3 0 2 4


Course Title Cyber Security and Cyber Laws

Course Outcomes: At the end of the course, students will be able to –

1. comprehend about various cyber security threats 2. identify the cyber laws in the context of modern security issues and threats

3. analyze the need of cyber security

4. apply security mechanism under various threat scenarios

Syllabus: Teaching

hours: Unit I Introduction: Computer security concepts, threats, attacks and assets, security

functional requirements, public and private key encryption techniques and algorithms, message authentication technique.

6

Unit II User Authentication: Mechanisms of authentication, password - based authentication,

token based authentication, biometric authentication, remote user authentication

3

Unit III Access Control and Database Security: Access control principles, subjects, objects

and access rights, DAC, database access control, inference attacks, database encryption, countermeasures against attacks on databases.

5

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Unit IV Malware: Types of malware, viruses, virus attacks, virus counter measures, worms,

bots, rootkits, Trojans

4

Unit V Attacks on Applications: Denial of service attacks, flooding attacks, distributed denial of service attacks, reflector and amplifier attacks, defenses against denial of service

attacks and responding, buffer overflow attack: stack overflow, defending against

buffer overflows, and other forms of overflow attacks, different kinds of injection

attacks, countermeasures against attacks on computer resources

11

Unit VI Models and Methods for Computer and Web Security: Bell-La Padula model for computer security, Biba model, Clark Wilson integrity

model, concept of trusted systems, web security: design issues, deployment

considerations, input validation, authentication, authorization, configuration management, sensitive data, session management, parameter manipulation, exception

management, auditing and logging.

7

Unit VII Cyber Crimes and Cyber Laws: Introduction to IT laws & cyber crimes – internet,

hacking, cracking, viruses, virus attacks, pornography, software piracy, intellectual

property, legal system of information technology, social engineering, mail bombs, bug exploits, and cyber security, IT act 2000

4

Unit VIII Modern Concerns for Computer and Cyber Security: Cloud security attacks, IOT

attacks, mobile app attacks, attacks on medical records, attack by/on smart phones,

social engineering attacks, introduction to IPSec.

5

Self-Study: The self-study contents will be declared at the commencement of semester. Around 10% of the questions will be asked from self-study contents.

Laboratory Work: Practical covering implementation of various computer security algorithms and simulating different

attacks using software tools is to be conducted. Minimum 6 practical should be carried out.

Suggested Readings^: 1. Pfleeger and Pfleeger, Security in Computing, Pearson Education. 2. William Stallings and Lawrie Brown, Computer Security Principles and Practices, Pearson

Education

3. Raghu Santanam, Sethumadhavan, Mohit Virendra, Cyber Security, Cyber Crime and Cyber Forensics: Applications and Perspectives, IGI Global.

4. Chris Davis, IT Auditing Using controls to protect Information Assets, TMH

5. Nina Godbole, Sunit Belapure Cyber Security, Wiley



https://www.amazon.in/s/ref=dp_byline_sr_book_1?ie=UTF8&field-author=Nina+Godbole&search-alias=stripbooks

Enclosure-XIV


NIRMA UNIVERSITY



Semester-IV

L T P C

3 0 2 4


Course Title Video Processing

Course Outcomes: At the end of the course, students will be able to -

1. apply video quality enhancement techniques and methods

2. analyze various video compression techniques and their applicability

3. create video processing system and compare video processing tools

4. analyse videos as three-dimensional signal in the spatio-temporal domain

Syllabus:

Teaching

hours: Unit I Introduction: Image definition, image processing, overview of applications, understanding of video, introduction to video processing , 3-d (spatio-temporal)

sampling and filtering, motion perception

4

Unit II Motion Detection and Estimation : Motion detection, 2-d motion estimation, 3-d

motion estimation, global motion estimation, block matching, phase correlation, optical flow via regularization, map estimation of dense motion

6

Unit III Video Enhancement and Restoration: Spatiotemporal noise filtering, coding

artefact reduction, super-resolution, scratch/dust removal, intensity flicker correction,

scratch removal

8

Unit IV Video Segmentation: Scene change detection, spatiotemporal change detection, motion segmentation, video object segmentation

7

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Unit V Motion Tracking in Video : Rigid object tracking(2d and 3d), articulated object

tracking (2d and 3d)

5

Unit VI Basic Video Coding: Digital video signals and formats, video compression

techniques, transform coding

8

Unit VII Video Compression Standards: MPEG-1 and MPEG-2, MPEG-4 Visual,

H.264/AVC, HEVC, and standard for modern digital video.

7

Self-Study: The self-study contents will be declared at the commencement of semester. Around 10% of the questions

will be asked from self-study contents.

Laboratory Work: Laboratory work will be based on above syllabus with minimum 5 experiments to be incorporated.

Suggested Readings^: 1. Murat Tekalp, Digital Video Processing, Prentice Hall

2. The Essential Guide to Video processing by Alan C. Bovik, Elsevier Science 3. Practical Image & Video Processing using MATLAB by Oge Marques

4. Digital Video Processing for Engineers: A Foundation for Embedded Systems Design By

Michael Parker, Suhel Dhanani 5. Video Processing and Communications, Yao Wang, Jorn Ostermann, Ya-Qin Zhang, Prentice

Hall, 2002

6. Video Coding for Mobile Communications, David Bull et al, Academic Press

L = Lecture, T = Tutorial, P = Practical, C = Credit__________________________________________


Enclosure-XIV


NIRMA UNIVERSITY



Semester-IV

L T P C

3 0 2 4


Course Name Blockchain Foundations


1. comprehend the structure of Blockchain networks 2. evaluate security issues relating to Blockchain and cryptocurrency

3. analyze and design the applications based on Blockchain technology

4. comprehend the use Blockchain in real world scenarios and applications

Syllabus: Teaching

hours: Unit I Introduction to Blockchain: Basics, history, conceptualization, digital money to

distributed ledgers, design primitives, protocols, security, consensus, permissions, and privacy.

5

Unit II Blockchain Architecture, Design and Consensus: Basic crypto primitives: hash,

signature, hash chain to Blockchain, basic consensus mechanisms, requirements for the

consensus protocols, PoW and PoS, scalability aspects of Blockchain consensus protocols.

8

Unit III Permissioned Blockchains: Design goals, consensus protocols for permissioned

Blockchains, Hyperledger fabric, decomposing the consensus process, Hyperledger

fabric components, chain code design, hybrid models (PoW and PoS)

10

Unit IV Public Blockchain: Block chains with smart contracts and Turing complete Blockchain scripting – issues of correctness and verifiability.

8

Unit V Blockchain cryptography: Different techniques for Blockchain cryptography, privacy

and security of Blockchain, multi-sig concept.

8

Unit VI Recent trends, research issues and Applications of Blockchain: Scalability, secure cryptographic protocols on Blockchain, multiparty communication, FinTech and Real

time case studies of different domains.

6

Self-Study:

Enclosure-XIV


The self-study contents will be declared at the commencement of semester. Around 10% of the questions will be asked from self-study contents.

Laboratory Work: Laboratory work will be based on the above syllabus with minimum 5 experiments to be incorporated.

Suggested Readings^: 1. Narayanan, Arvind, et al, Bitcoin and cryptocurrency technologies: a comprehensive

introduction. Princeton University Press.

2. Wattenhofer, Roger, The science of the blockchain, CreateSpace Independent Publishing

Platform

3. Bahga, Arshdeep, and Vijay Madisetti, Blockchain Applications: A Hands-on Approach, VPT 4. Nakamoto, Satoshi,Bitcoin: A peer-to-peer electronic cash system

5. Antonopoulos, Andreas M, Mastering Bitcoin: Programming the open blockchain, O'Reilly

Media, Inc 6. Diedrich, Henning, Ethereum: Blockchains, digital assets, smart contracts, decentralized

autonomous organizations, Wildfire Publishing (Sydney)

L=Lecture, T=Tutorial, P=Practical, C=Credit

^this is not an exhaustive list

Enclosure-XIV


NIRMA UNIVERSITY



Semester-IV

L T P C

3 0 2 4


Course Title Wireless Sensor Networks

Course Outcomes: At the end of the course, students will be able to

1. comprehend the distributed computation aspects of sensor networks

2. architect sensor networks for various application setups

3. explore the design space and conduct trade-off analysis between performance and resources

4. devise appropriate data dissemination protocols

Syllabus: Teaching

Hours: Unit I The Sensor Network Concept: Introduction, Applications, sensors, architectures, platforms for WSN, TinyOS and nesC, How to program WSN.

3

Unit II Wireless Communications: Link quality, shadowing and fading effects. Medium

Access - MAC protocols and energy efficiency.

6

Unit III Localization: Target tracking, localization and identity management, walking GPS,

range free solutions.

4

Unit IV Power Management: per node, system-wide, sentry services, sensing coverage.

5

Unit V Data Gathering: Tree construction algorithms and analysis - Asymptotic capacity-

lifetime optimization formulations- storage and retrieval, data collection and

processing, collaborative information processing and group connectivity.

12

Unit VI Routing: data centric, hierarchical, location-based, energy efficient routing etc.

5

Unit VII Deployment & Configuration: Sensor deployment, scheduling and coverage issues, self-configuration and topology control

5

Unit VIII Distributed Computation: Detection, estimation, and classification problems -

5

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Energy-efficient distributed algorithms.



Laboratory Work: Laboratory work will be based on above syllabus with at least 5 experiments to be incorporated.

Suggested Readings^: 1. Wireless sensor Networks by F. Zhao and L. Guibas, Morgan Kaufman

2. Protocols and Architectures of Wireless sensor networks by Karl H., Wiley

3. Wireless Sensor Networks: Technology protocols and applications by Kazem Sohrabi, Daniel Minoli, Taieb F. Znati



Enclosure-XIV


NIRMA UNIVERSITY


Master of Computer Applications

Semester – IV

L T P C

3 0 2 4


Course Name System and Network Security


1. comprehend principles and practices of computer and network security used in modern cyber-

physical systems 2. comprehend vulnerability assessment and prevention mechanisms in real-world systems

3. display in-depth understanding in computer security, network security, and managing security in

real-world problems

4. apply security control and policies

Syllabus: Teaching

Hours Unit I Cryptography basics: Symmetric and Asymmetric Cryptography, Modern ciphers, Hash functions, Digital signature algorithms, Key management.

12

Unit II Network security: Kerberos, SSL/TLS, E-Mail Security, IP security, Web security,

IDS/IPS.

12

Unit III Computer security: Threats to security, System and Software security; Virus,

Trojan, Worms, Malicious software, Firewalls.

10

Unit IV Security controls & policies: Access controls, Security policies, Standards, Ethics

in computer security.

11



Laboratory Work: Laboratory work will be based on applications of above syllabus with minimum 5 experiments to be

incorporated.

Suggested Readings ^: 1. M. Bishop, Computer Security: Art and Science, Pearson Education.

2. W. Stallings, Cryptography and Network Security, Prentice Hall

3. Kaufman, Perlman and Speciner, Network security, Pearson Education



Enclosure-XIV


NIRMA UNIVERSITY


Master of Computer Applications

Semester – IV

L T P C

3 0 2 4


Course Name Ethical Hacking and Privacy Laws


1. comprehend ethical hacking scenarios

2. identify various attacks and its consequences

3. analyze vulnerabilities of hardware and software 4. apply protection mechanisms to secure the systems technically & legally

Syllabus: Teaching

Hours Unit I Ethical Hacking Overview: Introduction to ethical hacking, what you can do legally,

what you cannot do legally

2

Unit II Network and Computer Attacks: malicious software (malware), protecting against

malware attacks, intruder attacks on networks and computers, addressing physical security

5

Unit III Footprinting and Social Engineering: using web tools for footprinting, conducting

competitive intelligence, using domain name system zone transfers, introduction of

social engineering

5

Unit IV Port Scanning: introduction of port scanning, understanding port-scanning tools,

conducting ping sweeps, understanding scripting

4

Unit V Desktop and Server OS Vulnerabilities: Windows OS vulnerabilities, best practices

for hardening windows systems, Linux OS vulnerabilities

4

Unit VI Hacking Web Servers: Understanding Web applications, understanding Web application vulnerabilities, tools for web attackers and security testers

4

Unit VII Network Protection Systems: understanding routers, understanding firewalls,

understanding intrusion detection and prevention systems, understanding honeypots

5

Unit VIII Hacking Wireless Networks: understanding wireless technology, understanding

wireless network standards, understanding authentication, understanding wireless

4

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hacking

Unit IX Cryptography: understanding cryptography basics, understanding symmetric and

asymmetric algorithms, understanding public key infrastructure, understanding cryptography attacks.

4

Unit X Privacy Laws: Concept of Privacy under Indian Constitution, Art. 21 of the

Constitution of India, Lawful interception under and Hacking: Cr.P.C., Telegraph’s

Act, IT Rules, Intermediary Rules, General Data Protection Regulation (GDPR), Data Protection Bill, 2019, Case Studies of various judgements.

8



Laboratory Work: Laboratory work will be based on applications of above syllabus with minimum 5 experiments to be

incorporated.

Suggested Readings ^: 1. Hands-on Ethical Hacking and Nework Defense by Simpson Michael T., Cengage publication 2. An Unofficial Guide to Ethical Hacking by Ankit Fadia, MacMillan

3. Gray Hat Hacking, The Ethical Hacker’s Handbook by Shon Harris, Allen Harper, Chris Eagle,

Jonathan Ness, Tata McGraw-Hill 4. Beginning Ethical Hacking with Python by Sanjib Sinha, Apress

5. The Right to Privacy in India: Concept and Evolution by Ravinder Kumar Gaurav Goyal



https://www.amazon.in/s/ref=dp_byline_sr_book_1?ie=UTF8&field-author=Ravinder+Kumar+Gaurav+Goyal&search-alias=stripbooks

nirma university · enclosure-xiv w.e.f. academic year 2020-21 onwards nirma university institute...

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