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Nirma University M.Tech. in CSE INS Syllabus



Appendix E
Page 1 of 10
Nirma University
Institute of Technology
Computer Science and Engineering Department
M.Tech. in CSE (INS)
Detailed Syllabus
Semester – I
3CS1101 High Speed Networks [3 - 1 4]
Learning Outcome
• Students would be able to describe and interpret the basics of high speed networking technologies.
• Students will be able to apply the concept learnt in this course to optimize and troubleshoot highspeed
network.
• Students will be able to demonstrate the knowledge of network planning and optimization.
• Students will be able to design and configure network that have outcome characteristics needed to
support a specified set of applications.
Syllabus
Introduction to Computer Networks, Networking Principles, Constant Bit Rate, Variable Bit Rate Network
Services, Network Elements, Multiplexing, Switching, Error Control, Flow Control
Introduction to High Speed Networks, Analysis of Network traffic using deterministic and stochastic Models,
Simulation tools, Tele-traffic engineering, Queuing Models
High Speed TCP Variants, Congestion Control in TCP/IP, ATM
High Speed LAN, Gigabit Ethernet, Distributed Queue Dual Bus (DQDB)
Protocols for QoS Support: IntServ, DiffServ, RSVP, MPLS
Optical Fiber Transmission, TCP/IP Performance over Optical Networks, Fiber Distributed Data Interface,
Switched Multi-Megabit Dual Service(SMDS)
Applications demanding high speed communication, Multimedia IP broadcasting, Error resilience in
Multimedia Transmission, Satellite Broadcasting
Self Learning Component
To be decided by course coordinator at the beginning of 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. along with
the related assessment component(s).
Laboratory Work
Above concepts are to be implemented and at least 5 experiments are to be carried out.
References
1. High-speed networks and Internets – Performance and quality of service by William Stallings
2. High Performance TCP/IP Networking: Concepts, issues and solutions: By Mahoob Hassan Raj and
Jain
3. High-speed networks: TCP/IP and ATM design principles by William Stallings
4. High speed networks by Marc Boisseau, Michel Demange, Jean-Marie Munier
5. Multimedia Communications: Applications, Networks, Protocols and Standards, Fred Halsall,
Addison –Wesley
3SP1103 Communication Skills for Engineers [- 1 - -]
Learning Outcome
• Students will be able to develop effective communication skills (spoken and written).
• They will be more aware of the dynamics behind effective communication
• Develop effective recruitment skills.
Appendix E
Page 2 of 10
• Conduct effective business correspondence.
• Students will be able to make professional presentations.
• Student will be able to shrug off the fear of public speaking to some extent.
Syllabus
Communication Skills: Communication cycle, types and flows of Communication, barriers to communication
Non-verbal Communication and Cross-cultural communication
Listening Skills: Types of listening, Barriers to effective listening, tips to improve listening skills
Business Communication: Various types of Letters and format, agenda and minutes of meeting, types of
memo and Resume and job application, Email etiquettes
Speaking Skills: Group Discussion, Personal Interview, Seminar Presentation
Writing Abstract, Research paper and Dissertation, Summarizing technical material , References and styling
Writing Business Proposal
Report Writing
References
1. Basic Communication Skills for Technology – Andrea J Rutherford (Person)
2. Technical Writing Process and Product – Shron J. Gerson (Person)
3. Business Communication, Lesiker and Petit: MCGraw Hill Publications
4. Business Correspondence and Report Writing – R.C. Sharma, Krishna Mohan (Tata McGraw)
3CS2102 Cryptography and Cryptanalysis [3 – 1 4]
Learning Outcomes
• Students will understand the concepts related to the basics of Network Security like Cryptography
• Students will be able to understand the mechanisms to be employed while trying to satisfy any of the
Security Service
Syllabus
Overview: Services, Mechanisms, Attacks, OSI Security Architecture, Model for Network Security
Classical Encryption Techniques: Symmetric Cipher Model, Substitution Techniques, Transposition
Techniques, Steganography
Block Ciphers and the Data Encryption Standard
Confidentiality using Symmetric Encryption
Public Key Cryptography and RSA
Key Management; Other Public Key cryptosystems
MAC and Hash Functions
Digital Signatures
IPSec: Architecture of IPSec, Encapsulating Security Payload, Authentication Header
Monoalphabetic unilateral substitution systems using standard cipher alphabets
Monoalphabetic unilateral substitution systems using mixed cipher alphabets
Monoalphabetic multilateral substitution systems: Generation, Recovery and Solutions of using Mixed Cipher
Alphabets
Polygraphic Substitution Systems: Characteristics and Identification of polygraphic substitution
Frequency distribution of English digraphs, trigraphs, tetragraphs, word and pattern tables, utility tables
Self Learning Component
To be decided by course coordinator at the beginning of 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. along with
the related assessment component(s).
Laboratory Work
Above concepts are to be implemented and at least 5 experiments are to be carried out.
Appendix E
Page 3 of 10
References
1. Cryptography and Network Security Principles and Practices by William Stallings
2. Basic Cryptanalysis Field Manual
3CS2103 Web Security [2 – 2 4]
Learning Outcomes
• Students will be able to understand the need of Security in our day to day communications.
• Obvious vulnerabilities in the network and computer system will be understood by the students.
• Students will be motivated to identify the loop holes in the technologies
Syllabus
Internet Security
Working of Internet: Working of TCP/IP, Working of World Wide Web
Working of Hackers: Invading PCs, Script Kiddies, Working of Personal Hacker Protection
Working of Spyware and Antispyware: Introduction to Spywares, Detection Escapism, Invading Privacy,
Hijacking home page and search pages, working of dialers, working of keyloggers and rootkits, following
spyware money trail, working of anti-spyware
Websites and privacy: Working of Cookies, Web bugs, Websites, Websites building personal profiles
Dangers of Internet Search: Working of Google, Individual Know-how
Phishing Attacks: Working of Phishing, following phishing money trail, protection against phishing attacks
Zombies and Trojan Horses: Working of Zombies and Bot Networks, Working of Trojan Horses, Zombie
Money Trail, Working of Zombie and Trojan Protection
Security Dangers in Browsers: Hackers exploit Networks, Protection against browser based attacks
Worms and viruses: Working of viruses and worms, antivirus software
Wi-Fi security dangers and protections: Working of Wi-Fi, Invading Wi-Fi Networks, hotspots, Evil Twin
Hacks and Protections
Bluetooth Security Dangers: Working of Bluetooth and hacking
Working of Spam: Dangers of spam, Hiding identity and identification, Working of Anti-spam software
Denial of Service Attacks and Protection
Introduction to Virtual Private Networks
Introduction to Web Blocking and Parental Controls
Working of Personal Firewalls and Proxies
Personal Privacy and Security
Working of Identity Thefts
Credit Card Security
Dangers of Data Mining
Dangers of Workplace Surveillance system
Hacking cell phones
Working of Biometrics
Working of Location Tracking
DNA Matching
Working of Airport Scanners and Screening Systems
Working of Wiretapping and Lie Detectors
Self Learning Component
To be decided by course coordinator at the beginning of 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. along with
the related assessment component(s).
Laboratory Work
Above concepts are to be implemented and at least 5 experiments are to be carried out.
Appendix E
Page 4 of 10
References
1. How Personal and Internet Security Work by Preston Galla, Que Publications
2. Computer Security Concepts, Issues and Implementation by Alfred Basta and Wolf Halton, Cengage
Learning
3CS2104 Mathematical Foundation for Network Security [3 1 - 4]
Learning Outcome
• Students will be able to understand the basic Mathematics related research in Networks.
• Students will be motivated to use the Mathematics related to Network in their Projects and Seminars
• Students will be able to apply these concepts in various Computer Science related applications
Syllabus
Linear Programming: Introduction, Formulation of LPP – Graphical Solution of LPP – Solution of LPP by
simplex method – Mixed Constraints, Dual of Linear programming problem application of linear
programming.
Finite fields: Groups, Rings and Fields, Modular Arithmetic, Euclidean Algorithm, Galois Field, Order of a
group, Multiplicative group, Order of an Element in the group, Order of an element in multiplicative group,
Generators, cyclic group, finding inverses, extended Euclidean Algorithm, Applications in RSA, Quadratic
Residue and its applications
Introduction to Number Theory: Prime Numbers, Fermat’s and Euler’s Theorem, Testing for Primality,
Chinese Remainder Problem
Number Theory Problems: Integer Fraction Problem, RSA Problem, Quadratic Residuosity Problem,
Computing Square Roots in Zn, Discrete Logarithm Problem, Diffie-Hellman Problem, Composite Moduli,
Computing Individual bits, Subset sum problem, Factoring Polynomials over finite fields
Prime Number Issues: Probabilistic Primality Tests, Primality Tests, Irreducible polynomials over ZP,
Generators and elements of higher order
Random Numbers: Random and Pseudo Random Bit Generation, Statistical Tests, Cryptographically Secure
pseudorandom number generation
Short path problems: Introduction to Shortest path problems, Method of finding the shortest path,
Processing/balancing & Time Scheduling.
Graph Theory: Graph isomorphism, sub graphs, paths, reachability and connectedness, cycles, matrix
representation of graphs, trees, labeled trees, tree searching, undirected trees, spanning trees of connected
relations, minimal spanning trees, Vertex Cover Problem, Graph Coloring Problems, Min-cut Max-flow
problems, Applications of Graph Theory in Network and Security
Self Learning Component
To be decided by course coordinator at the beginning of 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. along with
the related assessment component(s).
References
1. Kantiswarup and Manmohan Gupta – Operations Research, Publishers: S.Chand & Sons, New
Delhi
2. Cryptography and Network Security by William Stallings, PHI
3. S.D. Sharma – Operations Research, Publishers: Kedarnath Ramnath & Co. Meerut
4. H.A. Tana – Operations Research, Publishers: Prentice Hall, New Delhi
5. Discrete Mathematical Structures with Applications to Computer Science by Tremblay J.P.,
Manohar R., Tata McGraw-Hill.
6. ‘Graph Theory with applications to Engineering and Computer Science’ By Narsingh Deo
7. E-book on Handbook of Applied Cryptography by Alfred J Menezes, Paul C Van Oorschot and
Scott Vanstone
Appendix E
Page 5 of 10
3CS2202 Ethical Hacking [2 – 2 4]
Learning Outcome
• Students will be able to understand the Ethics behind hacking.
• Students will be possible to exploit the vulnerabilities related to Computer System and Networks
• Students will be exposed to the methodology to be followed on hacking a system.
Syllabus
Introduction to Ethical Disclosure: Ethics of Ethical Hacking, Ethical Hacking and the legal system, Proper
and Ethical Disclosure
Penetration Testing and Tools: Using Metasploit, Using BackTrack LiveCD Linux Distribution
Exploits: Programming Survival Skills, Basic Linux Exploits, Advanced Linux Exploits, Shellcode Strategies,
Writing Linux Shellcode, Basic windows Exploits
Vulnerability Analysis: Passive Analysis, Advanced Static Analysis with IDA Pro, Advanced Reverse
Engineering, Client-side browser exploits, Exploiting Windows Access Control Model for Local Elevation
Privilege, Intelligent Fuzzing with Sulley, From Vulnerability to Exploit
Malware Analysis: Collecting Malware and Initial Analysis, Hacking Malare
Self Learning Component
To be decided by course coordinator at the beginning of 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. along with
the related assessment component(s).
Laboratory Work
Above concepts are to be implemented and at least 5 experiments are to be carried out.
References
1. Gray Hat Hacking: The Ethical Hackers' Handbook by Shon Harris, Allen Harper, Chris Eagle and
Jonathan Ness - TMH Edition
2. Hacking: The Art of Exploitation by Jon Erickson - SPD
3CS1105 Comprehensive Assessment – I [- - - 1]
Learning Outcome
• Students will be able to realize the collective understanding of various courses studied in the
semester.
Syllabus
Student will be assessed on the basis of all the courses learned till end of the respective semester.
3SP1104 ICT Tools [- 1 - -]
At the end of the course, students will be:
• Aware of some of the latest ICT tools available for general purpose, academic and research use.
• Able to use ICT tools for application development / Research / Academic / Personal development
in the related field of study.
Syllabus
At least 5 tools have to be explored by the students as per their need to be decided in consultation with the
respective Course Coordinator for the respective Program.
Semester II
3CS2201 Securing Interconnecting Systems [2 – 2 4]
Learning Outcome
Appendix E
Page 6 of 10
• Students will be able to understand the various ways in which the interconnecting systems would be
connected.
• Students will be able to realize the need of systems from security point of view.
• Students will be able to design a Secured Network by configuring various elements of networks and
devices.
Syllabus
Introduction to System Interconnection, Planning-Establishing-Maintaining-Disconnecting Interconnect
Systems, Enterprise Systems - Heterogeneous and Interdependent
Resilience of the Internet Interconnection Ecosystem- Resilience and Efficiency, Service Level Agreements,
Reachability, Traffic and Performance, Regulation
Network Security and building Security insurance policies, Security Triangle, Responding to security incident,
Methods of network attacks, Evaluating network security, Disaster recovery considerations
Constructing a comprehensive network security policy, Threat and vulnerability analysis, Implementation of
controls and safeguard, Traffic/Log analysis, Audit planning and techniques
Securing Routers –authentication, authorization, Accounting, Detailed router auditing
Securing Switches - protecting layer2 switches, VLAN hopping, Switch spoofing, STP attacks, DHCP server
spoofing, Port Security
Firewalls – ACL, Traffic Filtering and traffic inspection, Alerts and audit trails, Security zones, Zone firewall
policies
Intrusion Prevention System (IPS) and Intrusion detection Systems (IDS)- Detection methods, Networkbased
Vs Host-based IPS, IDS and IPS appliances, Alarms
Securing Storage Area Networks- Overview of SAN, Fundamentals and benefits, SAN security fundamentals,
SAN Attacks, SAN Security Technologies
Securing VOIP-enabled Networks - Defining VOIP, VOIP benefits, VOIP Network, VOIP network
Components and VOIP protocols, Common voice vulnerabilities, Securing VOIP Network
Self Learning Component
To be decided by course coordinator at the beginning of 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. along with
the related assessment component(s).
Laboratory Work
Above concepts are to be implemented and at least 5 experiments are to be carried out.
References
1. CCSDS guide for secure system interconnection, NIST
2. Fundamentals of Network and Security by Eric Maiwald, TMH
3. CCNA Security Official Exam Certification Guide, Cisco Press
4. Various Research papers
3CS2203 Cyber Security and Laws [3 – 1 4]
Learning Outcome
• Students would be able to relate various methods used by the Forensic Department
• Students would be able to introduce a novel methodology of performing Cyber Forensics or System
Forensics
• Students will realize the Laws enforced by the Judiciary to handle cyber crimes and cyber frauds
• Students would realize how the digital evidences will be handled in any crime scene
Syllabus
Computer and Cyber Forensic Basics- Introduction to Computers, Computer History, Software, Hardware,
Appendix E
Page 7 of 10
Classification, Computer Input-Output Devices, Windows, DOS Prompt Commands, Basic Computer
Terminology, Internet, Networking, Computer Storage, Cell Phone / Mobile Forensics, Computer Ethics and
Application Programs, Cyber Forensic Basics- Introduction to Cyber Forensics, Storage Fundamentals, File
System Concepts, Data Recovery, Operating System Software and Basic Terminology
Data and Evidence Recovery- Introduction to Deleted File Recovery, Formatted Partition Recovery, Data
Recovery Tools, Data Recovery Procedures and Ethics, Preserve and safely handle original media, Document
a "Chain of Custody", Complete time line analysis of computer files based on file creation, file modification
and file access, Recover Internet Usage Data, Recover Swap Files/Temporary Files/Cache Files, Introduction
to Encase Forensic Edition, Forensic Tool Kit (FTK) etc, Use computer forensics software tools to cross
validate findings in computer evidence-related cases.
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 etc…
Cyber Forensics Investigation- Introduction to Cyber Forensic Investigation, Investigation Tools,
eDiscovery, Digital Evidence Collection, Evidence Preservation, E-Mail Investigation, E-Mail Tracking, IP
Tracking, E-Mail Recovery, Encryption and Decryption methods, Search and Seizure of Computers,
Recovering deleted evidences, Password Cracking
Cyber Security- Introduction to Cyber Security, Implementing Hardware Based Security, Software Based
Firewalls, Security Standards, Assessing Threat Levels, Forming an Incident Response Team, Reporting
Cyber crime, Operating System Attacks, Application Attacks, Reverse Engineering & Cracking Techniques
and Financial Frauds
Security Audit and Standards: Risk Assessment and Management, Asset Classification, Crisis Management
Plan, Resources Recovery Strategy, Security Testing, International Standards, Analysis and Logging, Security
Certification
Self Learning Component
To be decided by course coordinator at the beginning of 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. along with
the related assessment component(s).
Laboratory Work
Above concepts are to be implemented and at least 5 experiments are to be carried out.
References
1. Cyber Security, Cyber Crime and Cyber Forensics: Applications and Perspectives by Raghu
Santanam, Sethumadhavan, Mohit Virendra, IGI Global
2. IT Auditing Using controls to protect Information Assets by Chris Davis, TMH
3CS2204 Intrusion Detection Systems [3 – 1 4]
Learning Outcomes
• Students would be able to realize the research aspects in the field of Intrusion Detection Systems
• Students will be exposed to various aspects of IDS and IPS
• Students would be motivated to instigate various research projects in the area of IDS
Syllabus
Approaches in Anomaly based Intrusion Detection Systems: Introduction, Payload based vs. header based
approaches, setting up an ABS, PAYL & POSEIDON, Conclusions
Formal Specification for Fast Automatic Profiling of Program Behavior: Introduction, Related Works,
Methodology, Case Study, Remus configuration and conclusions
Learning Behavior Profiles from Noisy Sequences: Introduction, Learning by abstraction, Regular
Expressions, String Alignment and Flexible Matching, Learning Algorithm, Evaluation of Artificial Traces,
User Profiling
Appendix E
Page 8 of 10
Correlation Analysis of Intrusion Alerts: Introduction, Approaches based on similarity between Alert
Attributes, approaches based on predefined attack scenarios, approaches based on prerequisites and
consequences of attacks, approaches based on multiple information sources, Privacy issues in auto correlation
An approach to preventing, correlating, predicting multi-step network attacks: Introduction, Related work,
preliminaries, Hardening network to prevent multistep intrusions, Correlating and predicting multiple steps
attacks
Response: Bridging the link between Intrusion Detection alerts and security policies: Security Policy
Formalism, Threat Response system, From alerts to new policies
Intrusion Detection and Reaction: An integrated approach to network security: Proposed Framework,
Architecture for Intrusion Detection, Intrusion reactions, attack sessions, intrusion detection subsystem,
traffic classification and intrusion reaction, testing
Self Learning Component
To be decided by course coordinator at the beginning of 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. along with
the related assessment component(s).
Laboratory Work
Above concepts are to be implemented and at least 5 experiments are to be carried out.
References
1. Intrusion Detection Systems by Roberto Di Pietro and Luigi Mancini, Springer
2. Intrusion Detection Systems with Snort, Rafeeq Ur Rehman, Pearson Education, Prentice Hall
3. Guide to Intrusion Detection and Prevention Systems, National Institute of Science and Technology
3SP1204 Research Methodology [- 1 - -]
Learning Outcome
• Students would be able to ascertain basic objectives and motivation of research for societal
development
• Students would be able to critically evaluate current research and propose possible alternate
directions for further work
• Students would be aware of various data collection and analysis using qualitative methods and
modern data processing tools
• Students would be able to develop hypothesis and methodology for research
• Students would be able to comprehend and deal with complex research issues in order to
communicate their scientific results clearly for peer review
• Students would be able to document research work accomplished
Syllabus
Objective of research, motivation in research, types of research, interdisciplinary research, scientific methods
of research, criteria of good research, and characteristics of a good researcher.
Defining Research Problem: Art of literature review, user of ICT in effective literature review, formulation of
problem, formulation of hypothesis, developing research plan, meaning of research design, types of research
design, basic principles of experimental design, selection of relevant variables, validity of experiments.
Data Collection and Utilization: Types of data, methods & techniques of data collection, sampling,
characteristic of a good sample design, methods used in sampling, sampling errors, tests of hypothesis.
Quantitative Methods: Data presentation, statistical analysis and interpretation of data, types of analysis,
simple regression analysis, correlation, coefficient of determination (r2), z-test, t-test, ANOVA, Chi-square
test, multi-variate analysis of data, multiple regression.
Computer Application: Role of computer in research, data organization, software selection and its
applications, solving problems by using scientific software & tools, sample programs for analysis of data.
Thesis Writing and Presentation: Significance of writing thesis, different types of research writing; conference
Appendix E
Page 9 of 10
paper, journal paper, patents, thesis etc., different steps in writing thesis, layout of thesis, guidelines for
writing good thesis, precautions in writing thesis, presentations skills, defending the thesis.
References
1. Research Methodology: Methods & Techniques by C R Kothari, 2e, Wishwa Publication, New Delhi
2. Research Methodology by D K Bhattacharyya, 1 e, Excel Books, New Delhi, 2003
3. How to Research by Loraine Blaxter, Christina Hughes and Molcolm Tight, Viva Books Pvt. Ltd.,
New Delhi
4. Writing Your Thesis by Paul Oliver, Vistaar Pulication, New Delhi, 2006
5. The Research Student’s Guide to Success by Pat Cryer, Viva Books Pvt Ltd., New Delhi
3CS1201 Research Seminar [- - 1 1]
Candidates have to select any Research Topic as Self Study for their Research Seminar. They will be required
to present the progress of their Study in front of the Reviewing Panel at Regular intervals. During the final
review, students are required to submit the report of Seminar.
3CS1205 Comprehensive Assessment – II [- - - 1]
Learning Outcome
• Students will be able to realize the collective understanding of various courses studied in the
semester.
Syllabus
Student will be assessed on the basis of all the courses learned till end of the respective semester.
Semester – III
3CS1301 Project Part – 1 [- - 30 13]
Learning Outcome
• Students will be able to think creatively and independently.
• Students will be able to explore other facets of Research through new thinking and ideas.
• Students will be able to analyze systems and find problems.
• Students will be able to communicate effectively.
• Students will have an aptitude for optimization and enhancements in their area of specialization.
• Students will realize the need and importance of Research and the ethics involved in Research.
• Students will be better professionals.
Syllabus
The students will carry out a project with significant technical contribution either in the institute, any R&D
organization or Industry. At the end of the semester III, students will submit a report on the progress of his
work.
3SP1301 Practical Training [- - - -]
Learning Outcome
• Students will be oriented to decide upon the tools to be used in dissertation depending on their areas
of interest.
• Students will be ready for dissertation work.
Syllabus
During practical training of 4-6 weeks, students will learn required software tools/ methodologies, either in
industry/research organizations/academic institutions etc. or there will be a planned in-house training by our
faculty members/experts from other organizations, which will help them in their PG dissertation work.
Appendix E
Page 10 of 10
Semester – IV
3CS1401 Project Part – II [- - 30 14]
Learning Outcome
• Students will be able to think creatively and independently.
• Students will be able to explore other facets of Research through new thinking and ideas.
• Students will be able to analyze systems and find problems.
• Students will be able to communicate effectively.
• Students will have an aptitude for optimization and enhancements in their area of specialization.
• Students will realize the need and importance of Research and the ethics involved in Research.
• Students will be better professionals.
Syllabus
The student will continue the project work started in semester III and complete the work defined and submit
final dissertation for evaluation.

Nirma University M.Tech. in CSE Networking Technologies Syllabus



Appendix D
Nirma University
Institute of Technology
Computer Science and Engineering Department
M.Tech. CSE (Networking Technologies)
Detailed Syllabus
Semester – I
3CS1103 Data Structure and Algorithms [3 – 1 4]
Learning outcome
• Describe the usage of various data structures.
• Explain the operations for maintaining common data structures.
• Recognize the associated algorithms’ operations and complexity.
• Analyse and design efficient algorithms
Syllabus
Elementary Data Structures: Arrays, stack, queues, linked list, sorting techniques, Hash Tables, Binary Search
Trees, B-Trees, Binomial heaps
Mathematical Preliminaries: Algorithm analysis, Algorithm Proof Techniques, Analysis of Algorithms
Growth of Functions: Analyzing Control Structures, Using a barometer, Average case analysis, Amortized
Analysis, Solving recurrences
Greedy Algorithms: Making change, graphs and minimum spanning tree, knapsack problem, Scheduling
Divide and Conquer: General Template, various algorithm implementation eg Binary search , Heap sort,
Quick Sort, Finding the median, matrix multiplication
Dynamic Programming: Introduction of Dynamic Programming, Principle of Optimality, Comparison with
divide and conquer, single source shortest paths, Chained matrix multiplication
Graphs: Elementary Graph Algorithms, DFS, BFS, Backtracking, The knapsack problem, Eight Queens
problem, Branch and bound: The assignment problem
Computational Complexity and NP-Completeness: The classes of P and NP, Polynomial reductions, NPcomplete
problems, NP completeness proofs, NP hard problems, Non-Deterministic algorithms
Self Learning Component
To be decided by course coordinator at the beginning of 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. along with the
related assessment component(s).
Laboratory Work
Above concepts are to be implemented and at-least 5 experiments are to be carried out.
References
1. Fundamentals of Algorithmics, by Gilles Brassard and Paul Bratley, PHI
2. Introduction to Algorithms, by Thomas Cormen, Prentice-Hall India
3. Data structure and Algorithms, by Trembly and Sorenson
3CS3103 Communication Techniques [3 1 - 4]
Learning outcome
• Fundamentals in analog and digital communication system
• Application of probability and random processes in communication systems
• Learn various modulation techniques, multiplexing techniques
• Develop the ability to compare and contrast the strengths and weaknesses of various communication
Appendix D
Systems
• Understand the different channel coding methods
• Different radio propagation issues in communication systems
Syllabus
Probability and random variables, functions of one random variable, two random variables, stochastic
processes, stationary, non-stationary and ergodic processes,
Modulation and Coding Trade-Offs: Goals of the Communications system Designs- Error Probability Plane-
Nyquist Minimum Bandwidth- Shannon –Hartley Capacity theorem- Bandwidth Efficiency Plane- Modulation
and Coding Trade –Offs- Design and Evaluation of Digital Communication Systems- Bandwidth –Efficient
Modulation, Modulation and Coding for Band limited channels- Trellis-Coded Modulation .
Synchronization: Introduction- Receiver Synchronizer- Network Synchronization
Multiplexing and Multiple Access: Allocation of the Communications Resource- Multiple Access
Communications System and Architecture- Access Algorithms
Information and coding theory: Entropy, channel capacity, Vector spaces, basis, independence, linear codes,
block codes, convolutional codes, viterbi decoding, turbo codes, LDPC codes.
Fading Channels: Introduction - Characterizing Mobile-Radio Propagation- - Signal Time –Spreading,- Time
Variance of the Channel Caused by Motion- Mitigating the Degradation Effects of Fading- Key Parameters
Characterizing Fading Channels,- Mitigating the Effects of Frequency-Selective channel.
Self Learning Component
To be decided by course coordinator at the beginning of 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. along with the
related assessment component(s).
Tutorial
A minimum of eight assignments based on the topics of the syllabus and the recent trends in the area will be
assigned to the students.
References
1. Digital Communications: Design for the Real World, Andy Bateman, Prentice Hall
2. Digital communications: fundamentals and applications, Bernard Sklar, Prentice Hall
3. Digital Communications, Proakis, McGraw-Hill
4. Probability, random variables and stochastic processes, Papoulis, McGraw-Hill
5. Error control coding , Shu Lin, Pearson Education
3CS1101 High Speed Networks [3 - 1 4]
Learning Outcome
• Describe and interpret the basics of high speed networking technologies.
• Apply the concept learnt in this course to optimize and troubleshoot high-speed network.
• Demonstrate the knowledge of network planning and optimization.
• Design and configure network that have outcome characteristics needed to support a specified set of
applications.
Syllabus
Introduction to Computer Networks, Networking Principles, Constant Bit Rate, Variable Bit Rate Network
Services, Network Elements, Multiplexing, Switching, Error Control, Flow Control
Introduction to High Speed Networks, Analysis of Network traffic using deterministic and stochastic Models,
Simulation tools, Tele-traffic engineering, Queuing Models
High Speed TCP Variants, Congestion Control in TCP/IP, ATM
Appendix D
High Speed LAN, Gigabit Ethernet, Distributed Queue Dual Bus (DQDB)
Protocols for QoS Support: IntServ, DiffServ, RSVP, MPLS
Optical Fiber Transmission, TCP/IP Performance over Optical Networks, Fiber Distributed Data Interface,
Switched Multi-Megabit Dual Service(SMDS)
Applications demanding high speed communication, Multimedia IP broadcasting, Error resilience in
Multimedia Transmission
Self Learning Component
To be decided by course coordinator at the beginning of 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. along with the
related assessment component(s).
Laboratory Work
Above concepts are to be implemented and at-least 5 experiments are to be carried out.
References:
1. High-speed networks and Internets – Performance and quality of service by William Stallings, Prentice
Hall
2. High Performance TCP/IP Networking: Concepts, issues and solutions: By Mahoob Hassan Raj and Jain,
PHI
3. High-speed networks: TCP/IP and ATM design principles by William Stallings, Prentice Hall
4. High speed networks by Marc Boisseau, Michel Demange, Jean-Marie Munier, Wiley
5. Multimedia Communications: Applications, Networks, Protocols and Standards, Fred Halsall,
Addison –Wesley
3CS3104 Advance Computing Systems [3 - 1 4]
Learning outcome
• Fundamentals of parallel scientific computing
• Study various parallel architectures and programming models
• Understanding of various issues like load balancing, communication, and synchronization overhead for
HPC systems
• Knowledge of techniques/methods for energy aware computing
Syllabus
Requirements and General Issues of High performance computing,
Overview of Parallel Processing Concepts, Levels of parallelism (instruction, transaction, task, thread,
memory, function), Models(SIMD, MIMD, SIMT, SPMD, Dataflow Models, Demand-driven Computation
etc), Architectures: N-wide superscalar architectures, multi-core, multi-threaded
Scheduling Parallel jobs on HPC systems, Run time parallelization, Job and Resource Management Systems
Constructing Scalable Services, Performance Models and Simulations, Meta-Computing: Harnessing Informal
Supercomputers, Specifying Resources and Services in Meta-Computing Systems
Load Balancing over High Speed Networks, Network RAM, Distributed Shared Memory
Programming languages extensions for HPC, Execution profiling, timing techniques, and benchmarking for
modern single-core and multi-core processors
Power-Aware Computing and Communication: Power-aware Processing Techniques, Power-aware Memory
Design, Power-aware Interconnect Design, Software Power Management
Advanced Topics: Petascale Computing, Optics in Parallel Computing, Quantum Computers, Recent
developments in the area of High Performance Architectures and its impact on HPC
Appendix D
Self Learning Component
To be decided by course coordinator at the beginning of 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. along with the
related assessment component(s).
Laboratory Work
Above concepts are to be implemented and at-least 5 experiments are to be carried out.
References
1. High Performance Cluster Computing Architectures and Systems– By Rajkumar Buyya, Prentice Hall
PTR
2. Software Optimization for High Performance Computing: Creating Faster Applications" by K.R.
Wadleigh and I.L. Crawford, Hewlett-Packard professional books, Prentice Hall.
3. Sourcebook of Parallel Programming" by J. Dongara, I. Foster, G. Fox, W. Gropp, K. Kennedy, L.
Torczon, and A. White (eds), Morgan Kaufmann.
4. Advanced Computer Architecture: Parallelism, Scalability, Programmability", by Kai Hwang, McGraw
Hill
5. Petascale Computing: Algorithms and Applications, David A. Bader (Ed.), Chapman & Hall/CRC
Computational Science Series
6. Parallel Computer Architecture: A hardware/Software Approach, by David Culler Jaswinder Pal
Singh, Morgan Kaufmann
7. Scalable Parallel Computing", by Kai Hwang, McGraw Hill
8. Research Papers on advanced topics from Journals/Conference Proceedings
3CS1105 Information and Network Security [3 – 1 4]
Learning Outcome
• Students will be able to relate the Operating System Development from the Security Perspective
• Students will have an understanding about the various attacks and their counter-measures
• The subject will enable students to realize the Security concern from the initial phase of application
development.
Syllabus
Protection and in Operating systems, memory and addressing, protecting objects and files, user authentication,
security in distributed systems, design of trusted operating systems, encryption algorithms, Encrypted file
systems. Network security architectures, IP security, Firewall engineering, Encapsulating payloads,
authentication header, key exchange, Security in wireless networks access control, WPA, RSN, RADIUS etc.
Self Learning Component
To be decided by course coordinator at the beginning of 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. along with the
related assessment component(s).
Laboratory Work
Above concepts are to be implemented and at least 5 experiments are to be carried out.
References
1. Computer Security by Charles Pflegger and Pflegger
2. IPSec by N. Doraswamy and Dan Harkins
3. Cryptography and Network Security by William Stallings, PHI
Appendix D
3SP1103 Communication Skills for Engineers [- 1 - -]
Learning outcome
• Develop effective communication skills (spoken and written).
• They will be more aware of the dynamics behind effective communication
• Develop effective recruitment skills.
• Conduct effective business correspondence.
• Students will be able to make professional presentations.
• Student will be able to shrug off the fear of public speaking to some extent.
Syllabus
Communication Skills: Communication cycle, types and flows of Communication, barriers to communication.
Non-verbal Communication and Cross-cultural communication
Listening Skills: Types of listening, Barriers to effective listening, tips to improve listening skills.
Business Communication: Various types of Letters and format, agenda and minutes of meeting, types of
memo and Resume and job application, Email etiquettes
Speaking Skills: Group Discussion, Personal Interview, Seminar Presentation
Writing Abstract, Research paper and Dissertation, Summarizing technical material , References and styling
Writing Business Proposal
Report Writing
Self Learning Component
To be decided by course coordinator at the beginning of 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. along with the
related assessment component(s).
References
1. Basic Communication Skills for Technology – Andrea J Rutherford, Pearson
2. Technical Writing Process and Product – Shron J. Gerson, Pearson
3. Business Communication, Lesiker and Petit: MCGraw Hill Publications,
4. Business Correspondence and Report Writing – R.C. Sharma, Krishna Mohan, TMH
3CS1105 Comprehensive Assessment – I [- - - 1]
Learning Outcome
• Students will be able to realize the collective understanding of various courses studied in the semester.
Syllabus
Student will be assessed on the basis of all the courses learned till end of the respective semester.
3SP1104 ICT Tools [- 1 - -]
Learning Outcome
At the end of the course, students will be:
• Aware of some of the latest ICT tools available for general purpose, academic and research use.
• Able to use ICT tools for application development / Research / Academic / Personal development in
the related field of study.
Syllabus
At least 5 tools have to be explored by the students as per their need to be decided in consultation with the
respective Course Coordinator for the respective Program.
Appendix D
Semester – II
3CS3201 Network Embedded Systems [3 - 1 4]
Learning Outcome:
• Students will learn the fundamentals of embedded systems programming, real-time operating
systems
• Students will develop understanding of power-aware protocols for networks of small devices
• Exposure to a large set of newly developed methods in embedded systems and ubiquitous
computing
Syllabus
Introduction to Networked Embedded Systems, Embedded Distributed Systems, Embedded Processors
Overview, Operating Systems for Communication-Centric Devices, Sensor Network Applications, Sensor
Network Platforms, Embedded Systems Programming, Signal Behaviors and Sensor Interfaces, Location
Discovery Algorithms, Localization Techniques, Time Synchronization and Calibration, Radio Technologies
and Medium access protocols, Data Aggregation, Clustering and Aggregation, Mobility and Collaborative
Control, Collaborative Signal Processing, Robust Embedded Networking, IP-based Wireless Sensor
Networks, 6LoWPAN and IP Concepts, Constrained Application Protocol with 6LoWPAN, Embedded Web
Services, Security Issues and Data Integrity for Wireless Embedded Systems, Firmware and Applications for
the Internet of Things
Self Learning Component
To be decided by course coordinator at the beginning of 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. along with
the related assessment component(s).
Laboratory Work
Above concepts are to be implemented and at-least 5 experiments are to be carried out.
References
1. Principles of Embedded Network Design, Pottie and Kaiser, Cambridge University Press
2. Wireless Sensor Networks, An Information Processing Approach, Zhao and Guibas, Morgan
Kaufmann
3. Analysis, Instrumentation, and Visualization of Embedded Network Systems: A Testbed-based
Approach, Andrew Ryan Dalton, ProQuest
4. Embedded, Everywhere: A Research Agenda for Networked Systems of Embedded Computers,
National Academies Press
3CS3202 Information Retrieval System [3 - 1 4]
Learning outcome
• Develop understanding of concepts, algorithms, data/file structures necessary to design, and implement
Information Retrieval (IR) systems
• Learn methodology for the design and evaluation of information retrieval systems
• Learn about major types of information retrieval systems, the different theoretical foundations underlying
these systems
• Develop the practical skills for information retrieval systems
Appendix D
Syllabus
Overview of IR Systems, Architecture of information retrieval systems
Document Representation: Statistical Characteristics of Text, Basic Query Processing.
Data Structure and File Organization for IR, Retrieval Models: Similarity Measures and Ranking, Boolean
Matching, Vector Space Models, Probabilistic Models, Automatic Indexing and Indexing Models
Search and Filtering Techniques: Relevance Feedback, User Profiles, Collaborative Filtering
Automatic classification, Document and Term Clustering, Document Categorization
Heuristic classification, Nearest Neighbor, Naive Bayes Methods, Support Vector Machines
Machine Learning Techniques in IR, Neural Networks, Genetic Algorithms, Symbolic Learning
Indexing and storage issues, Information visualization and usage pattern analysis
IR Systems and the WWW, PageRank and Hyperlink Analysis, Search Personalization
N-Grams in Information Retrieval, Agent-based Information Retrieval
Parallel and Distributed IR, Multimedia IR: Models and Languages
Cross-Language and Multilingual Information Retrieval, Retrieval from noisy documents
Performance Evaluation of Information Retrieval Systems
Self Learning Component
To be decided by course coordinator at the beginning of 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. along with
the related assessment component(s).
Laboratory Work
Above concepts are to be implemented and at-least 5 experiments are to be carried out.
References
1. Introduction to Information Retrieval. C.D. Manning, P. Raghavan, H. Schütze, Cambridge UP
2. Modern Information Retrieval. R. Baeza-Yates, B. Ribeiro-Neto, Addison-Wesley
3. Information Retrieval: Algorithms and Heuristics, D.A. Grossman, O. Frieder, Springer
4. Language Modeling for Information Retrieval. W.B. Croft, J. Lafferty, Springer
5. Information Storage and Retrieval Systems. G. Kowalski, M.T. Maybury, Springer
6. A Semantic Web Primer Grigoris Antoniou and Frank van Harmelen, The MIT Press
7. Information Retrieval in Practice. B. Croft, D. Metzler, T. Strohman, Pearson Education
3CS3203 Wireless Networks [3 - 1 4]
Learning outcome
• Fundamentals of wireless communications: channel capacity, antennas, signal fading, encoding, spread
spectrum
• build understanding of all layers of wireless networking and the interactions between them
• Learn about security, energy efficiency, mobility, scalability, and their unique characteristics in wireless
networks
• Learn basics of Cellular networks and various issues like channel allocation, Capacity planning
• TCP/IP extensions for mobile and wireless networking
Fundamentals of Wireless Communication; Wireless LAN, PAN, WAN and MAN; Wireless Internet
Cellular Networks, GSM, Channel allocation, Network planning, Security, CDMA, DSSS, Spreading code, IS-
95 Standard, Mobile IP, Cellular IP, GPRS: Architecture and role of the components, Wireless Ad-hoc
Networks: Introduction; Game theory, MAC, Network and Transport layer protocols; QoS, Security and
Energy Management, Topology management, Mobility models
Self Learning Component
Appendix D
To be decided by course coordinator at the beginning of 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. along with
the related assessment component(s).
Laboratory Work
Above concepts are to be implemented and at-least 5 experiments are to be carried out.
References
1. Ad Hoc Wireless Networks – Architectures an Protocols by C. Siva Ram Murthy and B.S. Manoj,
Pearson Education
2. Wireless Ad hoc Network by Perkins, Pearson Education
3. Mobile Communications by Jochen Schiller, Pearson Education
4. Wireless Communications: Principles and Practice by Theodore Rappaport, Prentice Hall
3CS1201 Research Seminar [- - 1 1]
Candidates have to select any Research Topic as Self Study for their Research Seminar. They will be required
to present the progress of their Study in front of the Reviewing Panel at Regular intervals. During the final
review, students are required to submit the report of Seminar.
3SP1204 Research Methodology [- 1 - -]
Learning Outcome
• Ability to ascertain basic objectives and motivation of research for societal development.
• Ability to critically evaluate current research and propose possible alternate directions for further
work
• Awareness of various data collection and analysis using qualitative methods and modern data
processing tools
• Ability to develop hypothesis and methodology for research
• Ability to comprehend and deal with complex research issues in order to communicate their scientific
results clearly for peer review.
• Ability to document and present the research work accomplished
Syllabus
Objective of research, motivation in research, types of research, interdisciplinary research, scientific methods
of research, criteria of good research, and characteristics of a good researcher.
Defining Research Problem: Art of literature review, user of ICT in effective literature review, formulation of
problem, formulation of hypothesis, developing research plan, meaning of research design, types of research
design, basic principles of experimental design, selection of relevant variables, validity of experiments.
Data Collection and Utilization: Types of data, methods & techniques of data collection, sampling,
characteristic of a good sample design, methods used in sampling, sampling errors, tests of hypothesis.
Quantitative Methods: Data presentation, statistical analysis and interpretation of data, types of analysis,
simple regression analysis, correlation, coefficient of determination (r2), z-test, t-test, ANOVA, Chi-square
test, multi-variate analysis of data, multiple regression.
Computer Application: Role of computer in research, data organization, software selection and its
applications, solving problems by using scientific software & tools, sample programmes for analysis of data.
Thesis Writing and Presentation: Significance of writing thesis, different types of research writing; conference
Appendix D
paper, journal paper, patents, thesis etc., different steps in writing thesis, layout of thesis, guidelines for
writing good thesis, precautions in writing thesis, presentations skills, defending the thesis.
References:
1. Research Methodology: Methods & Techniques by C R Kothari, Wishwa Publication, New Delhi
2. Research Methodology by D K Bhattacharyya, Excel Books, New Delhi
3. How to Research by Loraine Blaxter, Christina Hughes and Molcolm Tight, Viva Books Pvt. Ltd.,
New Delhi
4. Writing Your Thesis by Paul Oliver, Vistaar Publication, New Delhi
5. The Research Student’s Guide to Success by Pat Cryer, Viva Books Pvt Ltd., New Delhi
3CS1205 Comprehensive Assessment – II [- - - 1]
Learning Outcome
• Students will be able to realize the collective understanding of various courses studied in the
semester.
Syllabus
Student will be assessed on the basis of all the courses learned till end of the respective semester.
Semester – III
3SP1301 Practical Training [- - - - ]
Learning Outcome
• Students will be oriented to decide upon the tools to be used in dissertation depending on their
areas of interest.
• Students will be ready for dissertation work.
During practical training of 4-6 weeks, students will learn required software tools/ methodologies, either in
industry/research organizations/academic institutions etc or there will be a planned in-house training by
our faculty members/experts from other organizations, that will help them in their PG dissertation work.
3CS1301 Project Part I [- - 30 13]
Learning Outcome
• Students will be able to think creatively and independently.
• Students will be able to explore other facets of Research through new thinking and ideas.
• Students will be able to analyze systems and find problems.
• Students will be able to communicate effectively.
• Students will have an aptitude for optimization and enhancements in their area of specialization.
• Students will realize the need and importance of Research and the ethics involved in Research.
• Students will be better professionals.
The students will carry out a project with significant technical contribution either in the institute, any R&D
organization or Industry. At the end of the semester III, students will submit a report on the progress of his
work.
Semester – IV
3CS1401 Project Part II [- - 30 14]
Learning Outcome
• Students will be able to think creatively and independently.
• Students will be able to explore other facets of Research through new thinking and ideas.
Appendix D
• Students will be able to analyze systems and find problems.
• Students will be able to communicate effectively.
• Students will have an aptitude for optimization and enhancements in their area of specialization.
• Students will realize the need and importance of Research and the ethics involved in Research.
• Students will be better professionals.
The student will continue the project work started in semester III and complete the work defined and
submit final dissertation for evaluation.

Nirma University M.Tech. in Computer Science and Engineering Syllabus



Appendix C
Nirma University
Institute of Technology
Computer Science and Engineering Department
M.Tech. in Computer Science and Engineering
Detailed Syllabus
Semester – I
3CS1101 High Speed Networks [3 - 1 4]
Learning outcome
• Describe and interpret the basics of high speed networking technologies.
• Apply the concept learnt in this course to optimize and troubleshoot high-speed network.
• Demonstrate the knowledge of network planning and optimization.
• Design and configure network that have outcome characteristics needed to support a specified set of
applications.
Syllabus
Introduction to Computer Networks, Networking Principles, Constant Bit Rate, Variable Bit Rate Network
Services, Network Elements, Multiplexing, Switching, Error Control, Flow Control
Introduction to High Speed Networks, Analysis of Network traffic using deterministic and stochastic Models,
Simulation tools, Tele-traffic engineering, Queuing Models
High Speed TCP Variants, Congestion Control in TCP/IP, ATM
High Speed LAN, Gigabit Ethernet, Distributed Queue Dual Bus (DQDB)
Protocols for QoS Support: IntServ, DiffServ, RSVP, MPLS
Optical Fiber Transmission, TCP/IP Performance over Optical Networks, Fiber Distributed Data Interface,
Switched Multi-Megabit Dual Service(SMDS)
Applications demanding high speed communication, Multimedia IP broadcasting, Error resilience in
Multimedia Transmission, Satellite Broadcasting
Self Learning Component
To be decided by course coordinator at the beginning of 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. along with the
related assessment component(s).
Laboratory Work
Above concepts are to be implemented and at-least 5 experiments are to be carried out.
References:
1. High-speed networks and Internets – Performance and quality of service by William Stallings
2. High Performance TCP/IP Networking: Concepts, issues and solutions: By Mahoob Hassan Raj and
Jain
3. High-speed networks: TCP/IP and ATM design principles by William Stallings
4. High speed networks by Marc Boisseau, Michel Demange, Jean-Marie Munier
5. Multimedia Communications: Applications, Networks, Protocols and Standards, Fred Halsall,
Addison –Wesley
3CS1103 Data Structure and Algorithms [3 – 1 4]
Learning outcome
Appendix C
• Describe the usage of various data structures.
• Explain the operations for maintaining common data structures.
• Recognize the associated algorithms’ operations and complexity.
• Analyze and design efficient algorithms
Syllabus
Elementary Data Structures: Arrays, stack, queues, linked list, sorting techniques, Hash Tables, Binary Search
Trees, B-Trees, Binomial heaps
Mathematical Preliminaries: Algorithm analysis, Algorithm Proof Techniques, Analysis of Algorithms
Growth of Functions: Analyzing Control Structures, Using a barometer, Average case analysis, Amortized
Analysis, Solving recurrences
Greedy Algorithms: Making change, graphs and minimum spanning tree, knapsack problem, Scheduling
Divide and Conquer: General Template, various algorithm implementation eg Binary search , Heap sort,
Quick Sort, Finding the median, matrix multiplication
Dynamic Programming: Introduction of Dynamic Programming, Principle of Optimality, Comparison with
divide and conquer, single source shortest paths, Chained matrix multiplication
Graphs: Elementary Graph Algorithms, DFS, BFS, Backtracking, The knapsack problem, Eight Queens
problem, Branch and bound: The assignment problem
Computational Complexity and NP-Completeness: The classes of P and NP, Polynomial reductions, NPcomplete
problems, NP completeness proofs, NP hard problems, Non-Deterministic algorithms
Self Learning Component
To be decided by course coordinator at the beginning of 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. along with the
related assessment component(s).
Laboratory Work
Above concepts are to be implemented and at-least 5 experiments are to be carried out.
References:
1. Fundamentals of Algorithmics, by Gilles Brassard and Paul Bratley
2. Introduction to Algorithms, by Thomas Cormen, Prentice-Hall India
3. Data structure and Algorithms, by Trembly and Sorenson
3CS1104 Computer Architecture [3 – 1 4]
Learning outcome
• A broad understanding of parallel computer architecture
• To the extent possible, an understanding of the current state-of-the-art in parallel computer
architecture.
Syllabus
Introduction, Flynn’s Taxonomy of Computer Architecture, Introduction to parallel processing, Parallelism in
uniprocessor systems, parallel computer structures, architectural classifications, Input and output subsystem,
virtual memory system, cache memories and management, I/O subsystems, Instruction-Level Parallelism and
its Exploitation, Limits on Instruction-Level Parallelism, Multiprocessors and Thread-Level Parallelism,
Memory Hierarchy Design, instruction and arithmetic pipelines, vector processors and vectorization methods,
SIMD array processors, SIMD computer organizations and interconnection networks, parallel memory
Appendix C
organizations, multiprocessor operating systems, control-flow versus data flow computers
Self Learning Component
To be decided by course coordinator at the beginning of 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. along with the
related assessment component(s).
Laboratory Work
Above concepts are to be implemented and at-least 5 experiments are to be carried out.
References:
1. Computer Architecture and Parallel Processing, K. Hwang and F. A. Briggs. McGraw Hill.
2. Advanced Computer Architecture and Parallel Processing, Hesham El-Rewini, Mostafa Abd-El-Barr,
Wiley
3. Advanced Computer Architecture, H. Stone. Addison Wesley,
4. Interconnection Network for Large Scale Parallel Processing, H. J. Siegel. McGraw Hill
5. Computer Architecture: A Quantitative Approach, 2nd Edition, J. L. Hennessy and D. A. Patterson,
Morgan Kaufmann.
6. Parallel Computer Architecture - A Hardware/Software Approach, D.E. Culler, J.P. Singh, and A.
Gupta, Morgan Kaufmann Publishers.
7. Principles and Practices of Interconnection Networks,W.J. Dally and B. Towles. Morgan Kaufmann
Publishers.
8. Multicore Processors and Systems, S.W. Keckler, K. Olukotun, and H.P. Hofstee. Springer.
9. Research papers from top conferences such as ISCA, HPCA, MICRO, and ASPLOS.
3CS1106 Software Engineering [3 - 1 4]
Learning Outcome
• This subject shall offer the skills for analysis, design, development testing & maintenance of software
towards beneficial for the student in respected profession.
• Students will get acquainted with systematic and organized approach for developing the software
fulfilling the needs of Industries.
• Student will learn an individual as well as teamwork approach for project development which is
essential for their career.
• By upholding the skills of all aspects of system & software production, student’s level of competence
will be enhanced.
Syllabus
Software process and lifecycle: Software Product, Product, Software Processes, , Study of different system
models, Critical Systems, Object Oriented Software Engineering, Formal Methods
Project Management Concepts, Planning and Scheduling, Team organization and people management, Risk
Management, metric and management, software configuration, Software Cost estimation
Software Requirements, Requirements Engineering Processes, Feasibility Studies, Validation and Management
Design principles: Architectural design. Distributed Systems Architecture, Object Oriented Design, Real Time
Software Design, User Interface Design.
Development and Testing: Rapid Software Development, Software Reuse with COTS
Technology, Component Base Software Engineering, Critical systems development, Clean Room software
Engineering ,System Testing
Verification and validation of Software: Software Inspections and Audit, Automates Analysis, CASE Tools
and
Critical systems validation
Software Quality Assurance, Quality Standards, Quality Planning and Control, Software Reliability Models,
Appendix C
Emerging Technologies: Security Engineering, Agile Methods, Service Oriented Software Engineering, Aspect
Oriented Software Development, Software Engineering Aspects of Programming Languages.
Self Learning Component
To be decided by course coordinator at the beginning of 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. along with the
related assessment component(s).
Laboratory Work
Above concepts are to be implemented and at least 5 experiments are to be carried out.
References
1. Software Engineering – Ian Sommerville (Addison – Wesley)
2. Software Engineering A Practitioners Approach – Roger Pressman (McGraw Hill Publication)
3. Fundamentals of Software Engineering – Rajib Mall (Prentice Hall of India)
4. Object Oriented Software Engineering A use case Approach -By Ivar Jacobson Pearson
3CS1107 Database Systems [3 – 1 4]
Learning outcome
• Understand database concepts and applications
• Understand storage organizations concepts
• Evaluate contemporary database architectures and database management issues
• Analyze and design efficient algorithms
Syllabus
Overview of Database Management System
Data storage: Using data storage efficiently, File Organization & Record formats, Heap sorted & Hashed Files,
other primary file of Indexing, Clustered-unclustered primary & secondary indexes, Multilevel Index, B+ Tree
Indexes & Operations, Hashing & Index,
Coping with Disk Failure, Index Structures for Single Dimensional and Multidimensional Databases Query
Execution, Algebra for Queries, Physical-Query-Plan-Operators, Algorithms for Database Operations,
Algorithms for Joins, Algorithms for Sorting, hash and Index Based Algorithms, Buffer Management, Parallel
Algorithms for Relational Operators.
Query Compiler: Algebraic Foundation for Improving Query Plans, Estimating Cost of Operations, Cost
Based Plan Selection, Choosing Order of Joins, Optimization of Queries for Parallel, Distributed,
Multidimensional and Text Database.
Coping with System Failure, Concurrency Control, Optimizing Locking Strategy, Handling Long Duration
Transactions, Distributed DBMS Reliability.
Information Integration, OLAP and Data Cube Operations.
Self Learning Component
To be decided by course coordinator at the beginning of 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. along with the
related assessment component(s).
Laboratory Work
Practicals will be based on various administrative and tuning aspects in any latest database system or may be
also conducted by assigning project based on above fundamentals.
Appendix C
References:
1. Data Base System Implementation, Garcia Molina, Ullman, Widom, Pearson education
2. Database System Concepts, Silberschatz ,Korth,Sudarshan, Mc Graw Hill
3. Fundamentals of Database System, Ramez Elmasri, Shamkant B Navathe, Pearson Education
4. Database Management Systems, Raghu Ramakrishnan & Johannes Gehrke, McGraw Hill
5. Principles of Distributed Database Systems, M.Tamer Ozsu, Patrick Valduriez, S.Sridhar, Pearson
Education
3SP1103 Communication Skills for Engineers [- 1 - -]
Learning outcome
• Develop effective communication skills (spoken and written).
• They will be more aware of the dynamics behind effective communication.
• Develop effective recruitment skills.
• Conduct effective business correspondence.
• Students will be able to make professional presentations.
• Student will be able to shrug off the fear of public speaking to some extent.
Syllabus
Communication Skills: Communication cycle, types and flows of Communication, barriers to communication.
Non-verbal Communication and Cross-cultural communication
Listening Skills: Types of listening, Barriers to effective listening, tips to improve listening skills.
Business Communication: Various types of Letters and format, agenda and minutes of meeting, types of
memo and Resume and job application, Email etiquettes
Speaking Skills: Group Discussion, Personal Interview, Seminar Presentation
Writing Abstract, Research paper and Dissertation, Summarizing technical material , References and styling
Writing Business Proposal
Report Writing
References:
1. Basic Communication Skills for Technology – Andrea J Rutherford (Person)
2. Technical Writing Process and Product – Shron J. Gerson (Person)
3. Business Communication, Lesiker and Petit: MCGraw Hill Publications, 1995
4. Business Correspondence and Report Writing – R.C. Sharma, Krishna Mohan (Tata McGraw)
3CS1105 Comprehensive Assessment - I [- - - 1]
Learning Outcome
• Students will be able to realize the collective understanding of various courses studied in the semester.
Syllabus
Student will be assessed on the basis of all the courses learned till end of the respective semester.
3SP1104 ICT Tools [- 1 - 0]
Learning Outcome
At the end of the course, students will be:
• Aware of some of the latest ICT tools available for general purpose, academic and research use.
• Able to use ICT tools for application development / Research / Academic / Personal development in
the related field of study.
Syllabus
Appendix C
At least 5 tools have to be explored by the students as per their need to be decided in consultation with the
respective Course Coordinator for the respective Program.
Semester – II
3CS1202 Real Time Systems [3 - 1 4]
Learning outcome
• Knowledge of software and system design process for microcontroller based real time systems
• Knowledge of the inner workings of real time operating systems
• Gaining experience in programming of real time systems
• Able to assess and design fault tolerant systems
Syllabus
Introduction: Issues in Real Time Computing, Structure of a Real Time System. Task Classes, Performance
Measures for Real Time Systems, and Estimating Program Run times. Task Assignment and Scheduling:
Classical Uniprocessor scheduling algorithms, UniProcessor scheduling of IRIS Tasks, Task Assignment,
Mode Changes, and Fault Tolerant Scheduling.
Programming Language and Tools – Desired Language characteristics, Data Typing, Control structures,
Facilitating Hierarchical Decomposition, Packages, Run time (Exception) Error handling, Overloading and
Generics, Multitasking, Low Level programming, Task scheduling, Timing Specifications, Programming
Environments, Run time Support.
Real Time Databases: Basic Definition, Real time Vs General Purpose Databases, Main Memory Databases,
Transaction priorities, Transaction Aborts, Concurrency Control Issues, Disk Scheduling Algorithms, Twophase
Approach to improve Predictability, Maintaining Serialization Consistency, Databases for Hard Real
Time systems.
Real Time Communication: Communications Media, Network Topologies Protocols, Fault Tolerant Routing.
Fault Tolerance Techniques: Fault Types, Fault Detection. Fault Error containment Redundancy, Data
Diversity, Reversal Checks, Integrated Failure handling.
Reliability Evaluation Techniques: Obtaining Parameter Values, Reliability Models for Hardware Redundancy,
Software Error models.
Clock Synchronization: Clock, A Nonfault Tolerant Synchronization Algorithm, Impact of Faults, Fault
Tolerant Synchronization in Hardware, Fault Tolerant Synchronization in Software.
Self Learning Component
To be decided by course coordinator at the beginning of 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. along with
the related assessment component(s).
Laboratory Work
Above concepts are to be implemented and at-least 5 experiments are to be carried out.
References:
Appendix C
1. Real Time Systems by C.M. Krishna, Kang G. Shin, McGraw Hill International Editions.
2. Real Time Computer Control - An Introduction by Stuart Bennett, Prentice Hall PTR.
3. Real time Micro Computer System Design – An Introduction by Peter D. Lawrence, McGraw Hill.
4. Introduction to real time software design by S.T. Allworth and R.N. Zobel, Macmillan.
5. An Introduction to Real Time Systems by R.J.A Buhur, D.L. Bailey, Prentice Hall International.
6. Real Time System Design and Analysis by Philip. A. Laplante, PHI.
3CS1203 Compiler Design [3 – 1 4]
Learning Outcome
• To enable the students to understand the structure and the basics of implementing compilers for
programming languages used in High Performance Computing
Syllabus
Overview of Lexical analysis and Syntax analysis, Intermediate code generation, Syntax directed translation,
symbol table management and error handlers, Introduction to various Intermediate representation and Run
time support, Control flow analysis, Data flow analysis, Dependence analysis and dependence graphs,
Introduction to optimizations, Redundancy elimination, Loop optimizations, procedure optimizations,
Register allocation, introduction to code scheduling, control flow and low level optimizations
Self Learning Component
To be decided by course coordinator at the beginning of 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. along with
the related assessment component(s).
Laboratory Work
Above concepts are to be implemented and at least 6 experiments are to be carried out.
References
1. Steven S. Muchnick.Advanced Compiler Design Implementation, Morgan Kauffman Publishers,
1997.
2. Wolfe. High Performance Compilers for Parallel Computing.
3. Zima and Chapman.Supercompilers for Parallel and Vector Computers.
4. Utpal Banerjee. Dependence analysis for supercomputing.
5. Wolfe. Optimizing Supercompilers for Supercomputers.
6. Ellis.Bulldog: A Compiler for VLIW Architectures
3CS1204 Distributed and Parallel Systems [3 - 1 4]
Learning Outcome
• Students will understand the programming aspects of Parallel Architectures
• Students will be able to correlate the engineering in high computing standards
Syllabus
Introduction to Parallel and Distributed Programming
Parallel Computing Architectures, Advanced Processors and Interconnects - Multicore Processors and Highbandwidth
Networks, Paradigms & Issues
Scalable Multiprocessors and Multicomputers - Distributed CC-NUMA and cluster Scalability.
Physical and Virtual Clusters - Server clusters, high availability, and Disaster Recovery
Processes, inter-process communication, multithreaded programming, thread synchronization, and
programming parallel virtual machines (PVM and MPI), Concurrent programming primitives (semaphores,
locks, monitors)
Shared Memory Models and Distributed Memory Models
Distributed Programming Issues and Algorithms
Appendix C
Remote procedure calls, process management, migration, mobile agents, distributed coordination, fault
tolerance
Distributed File Systems, synchronization, fault tolerance, coordination and consensus, replication and
sharing, security
Peer-to-Peer Computing Systems: - P2P systems, Overlay networks, and Content Distribution.
Distributed Computing Tools & Technologies - P2P systems, TeraGrid, MapReduce, Clusters, Hadoop,
Twister, Dryad, BigTable, GFS
Self Learning Component
To be decided by course coordinator at the beginning of 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. along with
the related assessment component(s).
Laboratory Work
Above concepts are to be implemented and at least 5 experiments are to be carried out.
References
1. Distributed Computing, Fundamentals, Simulations, and Advanced Topics by H. Attiya, J. Welch,
Wiley
2. Parallel Programming: Techniques and Applications Using Networked Workstations and Parallel
Computers, Barry Wilkinson and Michael Allen, Prentice Hall
3. Principles of Parallel Programming by Calvin Lin, Larry Snyder
4. K. Hwang and Z. Xu, Scalable Parallel Computing, McGraw-Hill
5. Ian Taylor: From P2P to Web Services and Grids, Springer-Verlag
6. F. Berman, G. Fox, and T. Hey (Editors), Grid Computing, Wiley
3CS1201 Research Seminar [- - 1 1]
Candidates have to select any Research Topic as Self Study for their Research Seminar. They will be required
to present the progress of their Study in front of the Reviewing Panel at Regular intervals. During the final
review, students are required to submit the report of Seminar.
3SP1204 Research Methodology [- 1 - -]
Learning outcome
• Ability to ascertain basic objectives and motivation of research for societal development.
• Ability to critically evaluate current research and propose possible alternate directions for further
work
• Awareness of various data collection and analysis using qualitative methods and modern data
processing tools
• Ability to develop hypothesis and methodology for research
• Ability to comprehend and deal with complex research issues in order to communicate their scientific
results clearly for peer review.
• Ability to document research work accomplished
Syllabus
Objective of research, motivation in research, types of research, interdisciplinary research, scientific methods
of research, criteria of good research, and characteristics of a good researcher.
Defining Research Problem: Art of literature review, user of ICT in effective literature review, formulation of
problem, formulation of hypothesis, developing research plan, meaning of research design, types of research
design, basic principles of experimental design, selection of relevant variables, validity of experiments.
Data Collection and Utilization: Types of data, methods & techniques of data collection, sampling,
characteristic of a good sample design, methods used in sampling, sampling errors, tests of hypothesis.
Appendix C
Quantitative Methods: Data presentation, statistical analysis and interpretation of data, types of analysis,
simple regression analysis, correlation, coefficient of determination (r2), z-test, t-test, ANOVA, Chi-square
test, multi-variate analysis of data, multiple regression.
Computer Application: Role of computer in research, data organization, software selection and its
applications, solving problems by using scientific software & tools, sample programmes for analysis of data.
Thesis Writing and Presentation: Significance of writing thesis, different types of research writing; conference
paper, journal paper, patents, thesis etc., different steps in writing thesis, layout of thesis, guidelines for
writing good thesis, precautions in writing thesis, presentations skills, defending the thesis.
References:
1. Research Methodology: Methods & Techniques by C R Kothari, 2e, Wishwa Publication, New Delhi
2. Research Methodology by D K Bhattacharyya, 1 e, Excel Books, New Delhi, 2003
3. How to Research by Loraine Blaxter, Christina Hughes and Molcolm Tight, Viva Books Pvt. Ltd.,
New Delhi
4. Writing Your Thesis by Paul Oliver, Vistaar Pulication, New Delhi, 2006
5. The Research Student’s Guide to Success by Pat Cryer, Viva Books Pvt Ltd., New Delhi
3CS1205 Comprehensive Assessment - II [- - - 1]
Learning Outcome
• Students will be able to realize the collective understanding of various courses studied in the
semester.
Syllabus
Student will be assessed on the basis of all the courses learned till end of the respective semester.
3SP1205 Network and Information Security [- 1 - 0]
Learning Outcome
At the end of the course, students will be able to:
• Understand the need of Security in our day to day communications.
• Identify obvious vulnerabilities in the network and computer system
• Motivated to identify and overcome the loop holes in the technologies
Syllabus
Internet Security: Working of Internet, Working of Hackers, Working of Spyware, Worms and Viruses,
Trojans and Zombies, Websites and privacy, Dangers of Internet Search, Phishing Attacks, Security Dangers
in Browsers, Wi-Fi security dangers and protections, Working of Spam, Denial of Service Attacks and
Protection, Introduction to Web Blocking and Parental Controls
Personal Privacy and Security: Working of Identity Thefts, Credit Card Security, Dangers of Workplace
Surveillance system, Hacking cell phones, Working of Biometrics, Working of Location Tracking, DNA
Matching, Working of Wiretapping and Lie Detectors
References
1. How Personal and Internet Security Work by Preston Galla, Que Publications
2. Computer Security Concepts, Issues and Implementation by Alfred Basta and Wolf Halton, Cengage
Learning
Semester – III
3SP1301 Practical Training [- - - - ]
Learning outcome
Appendix C
• Students will be oriented to decide upon the tools to be used in dissertation depending on their areas
of interest.
• Students will be ready for dissertation work.
Syllabus
During practical training of 4-6 weeks, students will learn required software tools/ methodologies, either in
industry/research organizations/academic institutions etc or there will be a planned in-house training by our
faculty members/experts from other organizations, which will help them in their PG dissertation work.
3CS1304 Project Part I [- - 30 13]
Learning outcome
• Students will be able to think creatively and independently.
• Students will be able to explore other facets of Research through new thinking and ideas.
• Students will be able to analyze systems and find problems.
• Students will be able to communicate effectively.
• Students will have an aptitude for optimization and enhancements in their area of specialization.
• Students will realize the need and importance of Research and the ethics involved in Research.
• Students will be better professionals.
Syllabus
The students will carry out a project with significant technical contribution either in the institute, any R&D
organization or Industry. At the end of the semester III, students will submit a report on the progress of his
work.
Semester – IV
3CS1401 Project Part II [- - 30 14]
Learning outcome
• Students will be able to think creatively and independently.
• Students will be able to explore other facets of Research through new thinking and ideas.
• Students will be able to analyze systems and find problems.
• Students will be able to communicate effectively.
• Students will have an aptitude for optimization and enhancements in their area of specialization.
• Students will realize the need and importance of Research and the ethics involved in Research.
• Students will be better professionals.
Syllabus
The student will continue the project work started in semester III and complete the work defined and submit
final dissertation for evaluation.

CWE/SANS Top 25

The 2011 CWE/SANS Top 25 Most Dangerous Software Errors is a list of the most widespread and critical errors that can lead to serious vulnerabilities in software. They are often easy to find, and easy to exploit. They are dangerous because they will frequently allow attackers to completely take over the software, steal data, or prevent the software from working at all.

Click on the links to download pdf:

Rank ID Name
[1] CWE-89 Improper Neutralization of Special Elements used in an SQL Command ('SQL Injection')
[2] CWE-78 Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')
[3] CWE-120 Buffer Copy without Checking Size of Input ('Classic Buffer Overflow')
[4] CWE-79 Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting')
[5] CWE-306 Missing Authentication for Critical Function
[6] CWE-862 Missing Authorization
[7] CWE-798 Use of Hard-coded Credentials
[8] CWE-311 Missing Encryption of Sensitive Data
[9] CWE-434 Unrestricted Upload of File with Dangerous Type
[10] CWE-807 Reliance on Untrusted Inputs in a Security Decision
[11] CWE-250 Execution with Unnecessary Privileges
[12] CWE-352 Cross-Site Request Forgery (CSRF)
[13] CWE-22 Improper Limitation of a Pathname to a Restricted Directory ('Path Traversal')
[14] CWE-494 Download of Code Without Integrity Check
[15] CWE-863 Incorrect Authorization
[16] CWE-829 Inclusion of Functionality from Untrusted Control Sphere
[17] CWE-732 Incorrect Permission Assignment for Critical Resource
[18] CWE-676 Use of Potentially Dangerous Function
[19] CWE-327 Use of a Broken or Risky Cryptographic Algorithm
[20] CWE-131 Incorrect Calculation of Buffer Size
[21] CWE-307 Improper Restriction of Excessive Authentication Attempts
[22] CWE-601 URL Redirection to Untrusted Site ('Open Redirect')
[23] CWE-134 Uncontrolled Format String
[24] CWE-190 Integer Overflow or Wraparound
[25] CWE-759 Use of a One-Way Hash without a Salt