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SRNMC Regulation-2016 Syllabus
SRI S. RAMASAMY NAIDU MEMORIAL COLLEGE (An Autonomous Institution Re-accredited with „A‟ Grade by NAAC)
SATTUR- 626203
M.PHIL (COMPUTER SCIENCE)
Syllabus and Regulations
Under
Choice Based Credit System (CBCS)
(Effective from the academic year 2015 – 2016)
REGULATIONS - 2015
SRNMC Syllabus
Objectives
The syllabus for M.Phil (Computer Science) under semester system has been so
designed that the students can have a clear idea on recent research developments in various
fields of Computer Science and Information Technology. The main objectives are:
To offer quality education and research providing wide scope to conduct substantial
empirical research.
To upscale the quality of research education in a splendid and instrumental manner.
To provide direction and guidance to enthusiastic graduate to convert their creative ideas
and plans, into a successful career in research and development.
To enhance the knowledge and skill of students in meeting with the needs of innovative
industrial research and development projects and also providing future scope for
research oriented studies and work.
The students with good acumen for computer science research skills can likely find
diplomatic international job opportunities.
To get prior idea on preparing research articles and dissertation in Computer Science.
To develop enough skills in Software tools so that students themselves able to prepare
articles and dissertation in Computer Science.
To impart the recent topics of research in Computer Science.
Eligibility
A Candidate who has qualified for the Master‟s Degree in any Faculty of
Madurai Kamaraj University or of any other University recognized by the Syndicate of
Madurai Kamaraj University as equivalent there to Computer Science shall be eligible
to register for the Degree of Master of Philosophy in Computer Science.
SRNMC Syllabus
A candidate who has qualified for Master‟s degree with not less than 55% of
marks in the concerned subject in any Faculty recognized by Madurai Kamaraj
University. Duration The duration of the M.Phil. Course shall be of two semesters for the full time programme.
Course of study
The course of study shall consist of
PART – I : Three Written Papers
PART – II : Dissertation.
The three papers under Part-I (First Semester) shall be:
Paper I : Research Methodology
Paper II: Advanced Techniques in Computer Science
Paper III: Optional Subject
LIST OF PAPERS
A SOFT COMPUTING
B DATA COMPRESSION
C KNOWLEDGE MANAGEMENT
D INFORMATION SECURITY
E ADVANCED NETWORKING
For Part-II (Second Semester):
SRNMC Syllabus
Dissertation and Viva-voce
Scheme of Examination
First Semester
Subject Subject
Code
Weekly
Contact
Hours
Library
Hours
Credits Exam
Hours
Marks
Int Ext Total
Paper I
Research
Methodology
MP16CS11 6 4 5 3 25 75 100
Paper II
Advanced
Techniques in
Computer
Science
MP16CS12 6 4 5 3 25 75 100
Paper III
Optional
Subject
MP16CSE11 6 4 5 3 25 75 100
Second Semester
Subject Subject
Code
Credits Marks
Int Ext Total
Dissertation MP16CSDN 7 75 75 150
Viva voce MP16CSVV 3 50 50
Total 10 200
Pattern of the Question Paper
Part A
Five questions (either or type).
Two questions from each unit. 5 x 6=30 Marks
SRNMC Syllabus
Part B
Three out of Five questions. 3 x 15=45 Marks
One question from each unit
-------------
TOTAL 75 Marks
-------------
Evaluation
1. Part I – Written papers
The performance of a scholar is evaluated in terms of percentage of marks.
Evaluation for each course shall be done by a continuous internal assessment by the
concerned teacher as well as by an End Semester Examination of 3 hours duration and
will be consolidated at the end of the course. The ratio of the marks to be allotted to
continuous internal assessment and to End Semester Examination is 25:75 (Internal 25 and External 75)
a) Maximum marks for test 15 marks
(Two tests and their average)
b) Maximum marks for seminar 5 marks
Activities
c) Maximum marks for Assignment 5 marks
------------
Total 25 marks
------------
SRNMC Syllabus
Passing Minimum
1. 50% of the aggregate (external+ internal).
2. No separate pass minimum for internal.
3. 34 marks out of 75 is the pass minimum for the External. 2. Part II - Dissertation
For carrying out the dissertation the mandatory requirement is strictly adhering to the rules of the college as given below:
Requirement
Every student is expected to give two seminars one concerning Review of Related
Literature within the four weeks from the beginning of the second semester and the other
on Data Analysis / Result just before the submission of the final draft of the dissertation
Submission
Candidates shall submit the Dissertations to the Controller of Examination not
earlier than five months but within six months in the full time programme. The above
said time limit shall start from 1st
of the month which follows after the month in which
Part-I examinations are conducted. If a candidate is not able to submit his/her
Dissertation within the period stated above, he/she shall be given an extension time of
three months in the first instance and another three months in the second instance with
penalty fees. If a candidate does not submit his Dissertation even after the two extensions,
his registration shall be treated as cancelled and he has to re-register for the course
subject to the discretion of the Principal. However the candidate need not write once
again the theory papers if he / she has already passed these papers.
SRNMC Syllabus
Requirement for valuation of Dissertation
One external examiner and the Research Adviser shall value the Dissertation. The
external examiner should be selected only from outside the college and shall be within
the colleges affiliated to Madurai Kamaraj University. In case of non-availability, the
panel can include examiners from the other university / colleges in Tamil Nadu. The
external examiner shall be selected from a panel of 3 experts suggested by the Research
Adviser. However, the Controller of Examination may ask for another panel if he deems
it necessary. Both the internal and external examiner will evaluate the Dissertation and
allot the marks separately. However the viva-voce will be done by both of them. The
average marks will be considered.
Viva-voce
The external examiner who valued the Dissertation and the Research Adviser
shall conduct the Viva-Voce for the candidate for a maximum of 50 marks. A Candidate
shall be declared to have passed in viva-voce if he secures not less than 50% of the marks
prescribed for Dissertation and 50% of the marks in the aggregate of the marks secured in
viva-voce test and Dissertation valuation. A student can undertake project in the second
semester whether or not he /she has passed the first semester.
SRNMC Syllabus
Internal Evaluation
Project Marks
Seminar on review of
related literature
15
Seminar on Data Analysis /
Results
25
Dissertation Evaluation 35
Total 75
External Evaluation
Marks
Dissertation Evaluation 75
Viva – voce 50
Total 125
SRNMC Syllabus
SRI S.RAMASAMY NAIDU MEMORIAL COLLEGE (An Autonomous Institution Re-accredited with „A‟ Grade by NAAC)
SATTUR - 626 203.
Department of Computer Science
(For those who are joining in 2015-2016 and after)
SYLLABUS
Programme: M.Phil (Computer Science) Subject Code :
Semester : I No. of Hours allotted : 6/Week
Subject : Core Paper I No. of Credits : 5
Title of the Paper: RESEARCH METHODOLOGY
Objectives:
To gain insights into how scientific research is conducted.
To help in critical review of literature and assessing the research trends, quality
and extension potential of research and equip students to undertake research.
To learn and understand the basic statistics involved in data presentation.
To identify the influencing factor or determinants of research parameters.
To test the significance, validity and reliability of the research results.
To help in documentation of research results.
To understand paradigms of algorithm design and techniques for analysis and to prove
the correctness of algorithms
Expected Outcome
Ability to critically evaluate current research and propose possible alternate
directions for further work
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.
SRNMC Syllabus
Unit I: RESEARCH METHODOLOGY AN INTRODUCTION
Meaning of Research: Objectives of Research – Type of Research – Research Approaches –
Significance of Research – Research Methods versus Methodology – Research and Scientific
Method – Research Process – Criteria of Good Research.
Defining the Research Problem: What is a Research Problem? - Selecting the Problem –
Necessity of Defining the Problem – Technique Involved in Defining a Problem.
Research Design: Meaning of Research Design – Need for Research Design – Features of a
Good Design – Important Concept Relating to Research Design – Different Research Design –
Basic Principle of Experimental Designs – Important Experimental Designs.
Unit II: RESEARCH DESIGN & DATA COLLECTION
Data Collection: Introduction – Experimental and Surveys – Collection of Primary Data –
Collection of Secondary Data – Selection of Appropriate Method for Data Collection
Data Preparation: Data Preparation Process – Missing Values and Outliers – Types of
Analysis – Statistics in Research.
Descriptive Statistics: Measures of Central Tendency – Measures of Dispersion – Measures of
Skewness – Kurtosis – Measures of Relationship – Association in case of Attributes – Other
measures.
Unit III: CASE STUDY & REPORT WRITING
Sampling and statistical Inference : Parameter and Statistic –Sampling and Non-sampling
Errors – Sampling Distribution –Degree of Freedom – Standard Error – Central Limit Theorem-
Finite Population Correction – Statistical Inference.
Interpretation and Report Writing: Meaning of Interpretation – Techniques of Interpretation –
Precaution in Interpretation – Significance of Report – Different Steps in Writing Report –
Layout of the Research Report – Types of Reports – Oral Presentation – Mechanics of Writing a
Research Report – Precautions for Writing Research Reports - Conclusion
Case Study – Research Methodology in Computer Science and Engineering. (Materials will be
provided)
SRNMC Syllabus
Unit IV: DATA STRUCTURES Linked Lists – Definition-Single linked list-Circular linked list-Double linked lists –
Applications of Linked Lists- Polynomial Representation – Memory Representation.
Tables – Rectangular Tables – jagged Tables – Inverted Tables –Hash tables.
Unit V: TREES & GRAPHS
Basic Terminologies – Definition and concepts – Representations of Binary Tree –
Operations on Binary tree – Types of Binary trees – Expression Tree – Binary Search Tree –
Heap Trees.
Graphs: Introduction – Graph Terminologies – Representation of Graphs– Applications
of Graph structures – Shortest path problem – Topological sorting – Minimum Spanning Trees.
Text Books:
1. C.R. Kothari, “Research Methodology Methods and Techniques”, New Age
International Publishers, Third Edition, 2014.
(Unit I, II & III)
2. Debasis Samanta “Classic Data Structures”, 2008, PHI.
(Unit IV & V)
Reference Books:
1. R.Panneerselvam, “Design and Analysis of Experiments”, PHI Learning Private
Limited, 2012.
2. R.Panneerselvam, “Research Methodology”, PHI Learning Private Limited, 2014.
3. Alfred V Aho, John E Hopcroft, “Design & Analysis of Computer Algorithms”,
Pearson Education, 2002.
4. A.A.Puntambekar, “Design & Analysis of Computer Algorithms”, Technical
Publications, 2010.
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5.Michael T. Goodrich and Roberto Tamassia, “Algorithm Design - Foundations,
Analysis & Internet Examples”, Wiley, 2002.
6. Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest and Clifford Stein,
“Introduction to Algorithms”, MIT Press, 2001.
Prepared By: Signature :
SRNMC Syllabus
SRI S.RAMASAMY NAIDU MEMORIAL COLLEGE
(An Autonomous Institution Re-accredited with „A‟ Grade by NAAC)
SATTUR-626 203.
Department of Computer Science
(For those who are joining in 2015-2016 and after)
SYLLABUS
Programme : M.Phil(Computer Science) Subject Code :
Semester : I No. of Hours allotted : 6/Week
Subject : Core Paper II No. of Credits : 5
Title of the Paper: ADVANCED TECHNIQUES IN COMPUTER SCIENCE
Objectives:
To analyze, design, develop and evaluate high-end computing systems.
To develop an overview of the field of image processing.
To understand the fundamental image processing algorithms and how to
implement them.
To gain experience in applying image processing algorithms to real problems
To introduce students to the basic concepts and techniques of Data Mining.
To develop skills of using recent data mining software for solving practical
problems.
To gain experience of doing independent study and research.
To identify new trends and evaluate emerging technologies
Expected Outcome:
As developers and specialists in high-end services and IT product
companies As academicians and researchers in India and abroad
SRNMC Syllabus
As consultants, solutions developers and entrepreneurs
World-wide demand for computing specialists in research labs and technology providers
UNIT – I DIGITAL IMAGE PROCESSING
Introduction- Fundamental Steps in Digital Image Processing – Components of Digital
Image Processing
Digital Image Fundamentals: Image sampling and Quantization - Basic Relationships
between Pixels- Simple Operations
Image Enhancement in Spatial Domain: Basic gray level Transformations, Histogram
processing- Arithmetic and logical Operations- Smoothing Spatial Filters- Sharpening Spatial
Filters
UNIT - II
Image Restoration: A model of Image degradation and restoration Process-Noise Models-
Mean Filters
Color Image Processing: Color image fundamentals - Color models-Color
Transformations
Image Compression: Image Compression Models – Error free Compression
UNIT – III DIP & DATA MINING
Morphological Image Processing - Image Segmentation
Data Mining:
What Motivated Data Mining? Why is it Important? – What is Data Mining? – Data
Mining – On What Kind of Data? – Data Mining Functionalities and Kind of Patterns Can Be
discovered – Classification of Data Mining Systems – Data Mining Task Primitives – Integration
of a Data Mining system with a Database or Data Warehouse System – Major Issues in Data
Mining
SRNMC Syllabus
UNIT - IV:
Data Preprocessing – Why Preprocess the Data? – Data Cleaning - Association Rules
Mining: Introduction- Basics – The task and a Naïve Algorithm –The Apriori Algorithm –
Improving the Efficiency of the Apriori Algorithm- Apriori-TID – Direct Hashing and Pruning –
Dynamic Item set Counting – Mining Frequent Patterns without Candidate Generation –
Performance Evaluation of Algorithms- Software for Association Rule Mining- Classification-
Introduction - Decision Tree – Building a Decision Tree – The Tree Induction Algorithm – Split
Algorithm Based on Information Theory – Split Algorithm Based on the Gini Index – Over
fitting and Pruning – Decision Tree Rules – Naïve Bayes Method – Improving Accuracy of
Classification Methods – Other Evaluation Criteria for Classification Methods – Classification
Software.
UNIT V: Cluster Analysis: What is Cluster Analysis? – Desired Features of Cluster Analysis –
Types of Data – Computing Distance – Types of Cluster Analysis Methods – Partitional
Methods – Hierarchical Methods – Density – Based Methods – Cluster Analysis Software -
WEB MINING: Introduction – Web Terminology and Characteristics – Locality and
Hierarchy in the Web - Web Data Mining – web content mining – web structure mining- web
usage mining - Recommender Systems: Introduction – Collaborative Recommendations.
.Text Books:
1. Rafael C. Gonzalez, Richard E. Woods, Digital Image Processing', Pearson, S
econd Edition.2002
Unit I : Chapter 1.4, 1.5, 2.4, 2.5, 3
Unit II : Chapter 5.1,5.2, 5.3.1, 6.1, 6.2, 6.5, 8.2, 8.4
Unit III : Chapter 9, 10
2. Jiawei Han and Micheline Kamber, “Data mining concepts and Techniques”,
Prentice Hall, second Edition, 2002. ( Unit III: Chapter 1, Unit IV : Chapter 2.1
& 2.3 )
3. G.K.Gupta, “Introduction to Data Mining with Case Studies”, PHI
Publications, 2012. ( Unit IV : Chapter 2 & 3, Unit V : Chapter 5 )
4. D.Jannach, M Zanker, Afelfenig, G.Friedrich, “Recommender Systems an
SRNMC Syllabus
Introduction”, Cambridge,First Edition,2011. ( Unit V : Chapter 1,2 )
Reference Books:
1. Rafael C. Gonzalez, Richard E. Woods, Steven L. Eddins, “Digital Image
Processing Using MATLAB”, Pearson Education, 2004.
2. Anil K.Jain,”Fundamentals of Dogital Image Processing”,Pearson 2002.
3. Jiawei Han and Micheline Kamber, “Data Image Processing”,
4. William K.Pratt, “Digital Image Processing”,John Wiley,New York,2002.
5. Milan Sonka et aI, “IMAGE PROCESSING,ANALYSIS AND MACHINE
VISION “,Brooke s/Cole,VikasPulishing House,2nd
edition,1999.
6. Arun K Pujari,”Data Mining Techniques”,University Press,III Edition,2009.
7. K.P.Soman, System Diwakar, Ajay, “Insight into Data Mining Theory and
Practice”, PHI Publications, 2012. Prepared By:
Signature :
SRNMC Syllabus
SRI S. RAMASAMY NAIDU MEMORIAL COLLEGE
(An Autonomous Institution Re-accredited with „A‟ Grade by NAAC) SATTUR - 626 203.
Department of Computer Science
(For those who are joining in 2015-2016 and after)
SYLLABUS
Programme : M.Phil (Computer Science) Subject Code :
Semester : I No. of Hours allotted : 6/Week
Subject : Optional Subject-Paper III-A No. of Credits : 5 Title of the Paper: SOFT COMPUTING
Objectives:
To familiarize with soft computing concepts.
To introduce the ideas of Neural Networks, Fuzzy Logic and use of heuristics
based on human experience.
To introduce the concepts of Genetic algorithm and its applications to soft
computing using some applications.
To impart the knowledge in Fuzzy Fundamentals.
To introduce some of the fundamental techniques and principles of neural
network systems and investigate some common models and their applications.
SRNMC Syllabus
UNIT – I: FUZZY LOGIC
Introduction - Classical Sets - Fuzzy Sets –classical relations and Fuzzy relations -
crisp relations - fuzzy relations - Fuzzy tolerance and Equivalence relations.
UNIT – II: Properties of Membership functions - Fuzzification – Defuzzification -
Fuzzy Systems-Development of Member ship functions.
UNIT – III: NEURAL NETWORKS
Introduction - Artificial Neural Networks - Historical developments of Neural
Networks – Biological Neural Networks –Comparison between the Brain and the
Computer– Basic Building blocks of Artificial Neural Networks- Artificial Neural
Networks Terminology-Fundamental Models of Artificial Neural Networks- Mc-
Culloch-Pitts Neuron Model- Learning Rules- Hebb Net-Perceptron Network- Back
Propagation Network (BPN).
UNIT – IV: ARTIFICIAL INTELLIGENCE AND EXPERT SYSTEMS
Introduction : Problem Definition – Search Strategies – Characteristics – Game
Playing - Knowledge representation – Expert System – Roles of Expert System –
Knowledge acquisition, Meta knowledge – Heuristics knowledge – Interface : Backward
and forward chaining – Fuzzy reasoning – Learning – Adaptive Learning – Types of
Expert System : MYSIN, PIP, INTERNIST, DART, XOON, Expert Systems Shells.
UNIT – V: GENETIC ALGORITHM
Introduction – Basic Operators and Terminologies in GAs – Traditional Algorithm
vs. Genetic Algorithm – Simple GA – General Genetic Algorithm – The Schema
Theorem – Classification of Genetic Algorithm – Holland Classifier Systems – Genetic
SRNMC Syllabus
Programming – Application of Genetic Algorithm.
Text Books:
1. Timothy J. Ross, ”Fuzzy Logic with Engineering Applications”,John Wiley &
Sons, Third Edition 2010. ( Unit I & II).
2. S. N. Sivanandam, S. Sumathi, S.N. Deepa, “Introduction to Neural Networks
using MATLAB 6.0“, Tata McGraw-Hill, New Delhi, 2006. ( Unit III ).
3. Elaine Rich and Kevin Knight, “Artificial Intelligence”, McGraw-Hill, Second
Edition, 1991. ( Unit IV ).
4. S. N. Sivanandam, S.N. Deepa, “Principles of Soft Computing”, Wiley-India, 2014.
(Unit V ).
SRNMC Syllabus
Reference Books:
1. Satish Kumar, “Neural Networks – A Classroom approach”, Tata McGraw-Hill,
New Delhi, 2007.
2. Martin T. Hagan, Howard B. Demuth, Mark Beale, “Neural Network Design”,
Thomson Learning, India, 2002.
3. B. Kosko, “Neural Network and fuzzy systems”, PHI Publications, 1996.
4. Klir & Yuan, “Fuzzy sets and fuzzy logic – theory and applications”, PHI
Publications, 1996.
5. Melanie Mitchell, “An introduction to genetic algorithm”, PHI Publications,
India, 1996.
6. David E.Goldberg, “Genetic Algorithms in Search Optimization and Machine
Learning”, Pearson Education, 2007.
7. N.P. Padhy, “Artificial Intelligence and Intelligent Systems”, Oxford
University Press, 2005.
8. Yegnanarayana, “ArtificialNeuralNetworks”, PHI Publications, 2008.
9. Melanie Mitchell, “An Introduction to Genetic Algorithms”, MIT Press, First
Edition. 1998.
10. Nildon, N.J. Springer Verlag, “Principles of Artificial Intelligence”, Morgan
Kaufmann Publishers, 1980.
Prepared By:
Signature :
SRNMC Syllabus
SRI S.RAMASAMY NAIDU MEMORIAL COLLEGE (An Autonomous Institution Re-accredited with „A‟ Grade by NAAC)
SATTUR-626 203.
Department of Computer Science
(For those who are joining in 2015-2016 and after)
SYLLABUS
Programme : M.Phil (Computer Science) Subject Code :
Semester : I No. of Hours allotted : 6/Week
Subject : Optional Subject-Paper III-B No. of Credits : 5
Title of the Paper: DATA COMPRESSION
Objectives:
To provide conceptual understanding, and hands-on experience, of the state-of-
the-art compression algorithms and approaches.
To introduce the knowledge in data compression techniques, and to study
different methods of compression and its techniques.
UNIT-I: INTRODUCTION
Compression Techniques – Lossy compression & Lossless compression,
modeling and compression Mathematical modeling for Lossless compression- Physical
models, probability models, Markov Models and composite source models. Mathematical
modeling for Lossy compression – physical models, Probability models and linear
systems models.
UNIT – II: DIFFERENT METHODS OF COMPRESSION
Basic Techniques: Run length encoding, RLE Text compression, RLE image
SRNMC Syllabus
compression and scalar quantization.
Statistical Methods: Information theory concepts, Huffman coding, Adaptive
Huffman coding, facsimile compression Arithmetic coding and Adaptive, Arithmetic
coding and Text compression.
SRNMC Syllabus
Dictionary methods: String compression, LZ 77, LZSS, LZ78, LZW, UNIX
compression, GIF image, ARC and PKZIP, Data compression patterns.
Wavelet methods: Fourier Image compression, Multi Resolution decomposition and JPEG 2000.
UNIT-III: IMAGE COMPRESSION
Intuitive Methods, Image Transforms, JPEG, Progressive Image compression,
Vector quantization, Adaptive Vector Quantization, Block Matching, Block Truncation
coding. Context Tree weighting, Block Decomposition, Binary Tree predictive coding,
Quad Trees and Finite Automata Methods.
UNIT –IV: VIDEO COMPRESSION
Analog Video, Composite and Components Video, Digital Video, Video
compression, MPEG and H.261.
UNIT – V: AUDIO COMPRESSION
Sound, Digital Audio, The Human Auditory System, µ -Law and A-Law
compounding, ADPCM Audio compression and MPEPG-1 Audio Layers.
Text Books:
1. David Salomon, “Data compression – The Complete Reference”, Springer
Publications, Fourth Edition, 2007. (Unit I & II)
2. Mark Nelson and Jean-Loup Gailly, “The Data Compression Book”, BPB
Publications, Second Edition, 1995. ( Unit III )
3. Khalid Sayood, “Introduction to Data Compression”, Harcout India(P) Ltd,
Third Edition, 2006. ( Unit IV & V)
SRNMC Syllabus
Reference Books:
1. Gersho and R. M. Gray, “ Vector Quantization and Signal Compression”, The
Springer International Series in Engineering and Computer Science),1992
2. G. Held and T. R. Marshall, “Data and Image Compression: Tools and
Techniques”, Wiley , Fourth Edition,1996
3. D. Hankerson, P. D. Johnson, and G. A. Harris, “Introduction to Information
Theory and Data Compression”, Chapman and Hall, Second Edition, 2003.
Prepared By:
Signature :
SRNMC Syllabus
SRI S.RAMASAMY NAIDU MEMORIAL COLLEGE
(An Autonomous Institution Re-accredited with „A‟ Grade by NAAC) SATTUR-626 203.
Department of Computer Science
(For those who are joining in 2015-2016 and after)
SYLLABUS
Programme : M.Phil (Computer Science) Subject Code :
Semester : I No. of Hours allotted : 6/Week
Subject : Optional Subject-Paper III-C No. of Credits : 5
Title of the Paper: Knowledge Management
Objectives:
To understand organizational contexts of technological infrastructures and
emerging technological frameworks for electronic information and knowledge
management systems.
To identify and select from appropriate strategic components & tools for
designing and implementing an information and knowledge management system.
To develop intelligent applications using Knowledge Management.
UNIT - I
Basics - What is Knowledge Management? - Key Challenges - KM Life Cycle -
Understanding Knowledge – Definitions - Cognition and Knowledge Management -
Data, Information, and Knowledge - Types of Knowledge - Expert Knowledge.
SRNMC Syllabus
UNIT - II
Knowledge Management System Life Cycle - Challenges in Building KM
Systems - Conventional Versus KM System Life Cycle - KM System Life Cycle -
System Justification - Role of Rapid Prototyping - Role of Knowledge Developer – User
Training.
UNIT- III
Knowledge Creation - Nonaka‟s Model of Knowledge Creation and Transformation - Knowledge Architecture - Capturing Tacit Knowledge – Evaluating the
Expert – Developing a relationship with Expert –Knowledge Creation - Nonaka‟s Model
of Knowledge Creation and Transformation - Knowledge Architecture - Capturing Tacit
Knowledge – Evaluating the Expert – Developing a relationship with Expert. UNIT - IV
Knowledge Codification - Codification Tools and Procedures - Knowledge
Developers Skill Set - Knowledge Transfer - Transfer Methods - Role of the Internet in
Knowledge Transfer - Knowledge Transfer in the E-World - E-Business – KM Tools -
Personal KM Tools, What next – from GUI to CIM, Software – Knowledge Technologies
:- State of Technology, KM Gets Unconventional, Application is the Key, Content Mgmt,
Technology components of KM, ERP and BPR, Meta-data Architecture. UNIT - V
Knowledge Management Tools and Knowledge Portals - Portals Basics -
Business Challenge - Knowledge Portal Technologies - Ethical and Legal Issues -
Knowledge Owners - Legal Issues - The Ethical Factors – Futuristic KM.
Text Book:
1. Elias M.Awad, Hassan M.Ghaziri, ”Knowledge Management”, Pearson Education, Second Edition, 2004.
Reference Books:
SRNMC Syllabus
1. A Thothathri Raman, “Knowledge Management a Resource Book”, EXCEL
Books, 2004.
2. Kai Mertins, Peter Heisig, Jens Vorbeck,”Knowledge Management: Concepts
and Best Practices”, Springer Publications, Second Edition, 2003.
3. Amrit Tiwana, “The Essential Guide to Knowledge Management – E-Business
and CRM Applications”, Pearson Education Asia, 2004 .
Prepared By:
Signature :
SRNMC Syllabus
SRI S.RAMASAMY NAIDU MEMORIAL COLLEGE
(An Autonomous Institution Re-accredited with „A‟ Grade by NAAC)
SATTUR-626 203.
Department of Computer Science
(For those who are joining in 2015-2016 and after)
SYLLABUS
Programme : M.Phil (Computer Science) Subject Code :
Semester : I No. of Hours allotted : 6/Week
Subject : Optional Subject-Paper III-D No. of Credit : 5 Title of the Paper: INFORMATION SECURITY
Objectives:
To understand information security‟s importance in our increasingly computer-
driven world.
To master the key concepts of information security and how they work.
To develop a “security mindset:” learn how to critically analyze situations of
computer and network usage from a security perspective, identifying the salient
issues, viewpoints, and trade-offs.
To examine, understand and explain key aspects of information security.
To identify and prioritize information assets and threats to them.
To define an information security strategy and architecture.
To plan for and respond to intruders in an information system
To describe legal and public relations implications of security and privacy issues.
To present a disaster recovery plan for recovery of information assets after an
Incident.
SRNMC Syllabus
UNIT - I
Conventional Encryption : Classical Technique – Modern technique –
Algorithms; Public Key Cryptography : Public Key Cryptography – Introduction to
Number Theory – Message Authentication and Hash Function – HASH and MAC
Algorithm – Digital Signature and Authentication protocol.
UNIT - II
Network Security Practice: Authentication Application – Electronic Mail Security – IP Security Program Security and System Security: Secure programs – No malicious
program errors – viruses and Worms – Memory and address protection – control access
to general objects – File protection mechanism – user authentication – Trusted operating
system design and assurance – Intrusion Detection system.
UNIT - III
System Security and Web Security: Intruders,– Firewall - Managing Access –
Password management - Web Security requirements – SSL and TLS – SET; Client Side
Security : Using SSL – Active Content – Web Privacy. Database Security: The
Database as Networked Server Securing database-to-database communication –
Reliability and Integrity of database – sensitive data – inference multilevel databases.
UNIT - IV
Wireless Network Security: Mobile Security – Encryption Schemes in WLANs –
Basic approach to WLAN security and Policy Development – WLAN intrusion process –
WLAN security solutions. Digital Watermarking and Steganography: Models of
Watermarking – Basic Message Coding – Watermark Security – Content Authentication – Steganography.
SRNMC Syllabus
UNIT - V
Cyber Crimes: Introduction – computer crime and cyber crimes; Classification
of cyber crimes, Cyber crime and Related Concepts: Distinction between cyber crime
and conventional crimes, Reasons for commission of cyber crime, Cyber forensic :
Cyber criminals and their objectives, Kinds of cyber crimes – cyber stalking; cyber
pornography; forgery and fraud; crime related to PRs; Cyber terrorism; computer
vandalism, Regulation of cyber crimes: Issues relating to investigation, Issues relating to
Jurisdiction, Issues relating to Evidence , Relevant provisions under Information
Technology Act, 2000, Indian Penal Code, Pornography Act and Evidence Act etc.
Text Books:
1. Charrles P. Pfleeger, Shari Lawrence Pfleegner, “Security in Computing”, Prentice
Hall of India, 2007. (Unit I)
2. William Stallings, “Cryptography and Network Security”, Pearson, Fifth Edition,
2010. ( Unit II )
3. Lincoln D. Stein, “Web Security”, Addison Wesley, 1999. ( Unit III )
4. Ingemar J.Cox, Matthew L. Miller Jeffrey A.Bloom, Jessica Fridrich,Ton
Kalker,“Digital Watermarking and Steganography”, Elsevier, Second Edition,
2007. (Unit IV)
5. Dr.R.K.Tiwari, P.K.Sastri, K.V.Ravikumar, “Computer Crime and Computer
Forensics”, Selective Publishers, First Edition, 2002. (Unit V)
Reference Books:
1. Basin, David, Paterson, Kenny,”Information Security and
Cryptography”,Springer,ISSN: 1619-7100.
2. Harold F. Tipton, Micki Krause “ Information Security Management Handbook”,
Auerbach Publication,Taylor and Francis Group, Sixth Edition ,2007
SRNMC Syllabus
3. Michael E. Whitman, Herbert J. Mattord.”Principles of Information Security”,
Cengage Learning, 2010
4. John W.Rittinghouse, James F.Ransome, “Wireless Operational Security”,
Elsevier, 2004.
Prepared by:
Signature :
SRNMC Syllabus
SRI S.RAMASAMY NAIDU MEMORIAL COLLEGE (An Autonomous Institution Re-accredited with „A‟ Grade by NAAC)
SATTUR-626 203.
Department of Computer Science
(For those who are joining in 2015-2016 and after)
SYLLABUS
Programme : M.Phil (Computer Science) Subject Code :
Semester : I No. of Hours allotted: 6/Week
Subject : Optional Subject-Paper III-E No. of Credits : 5
Title of the Paper: ADVANCED NETWORKING
Objectives:
To address quality of service issues and network reliability for transmission of
real-time information.
To look at the possibilities and limitations of cloud computing and Grid computing
networking and its applications.
To inculcate the challenges of security in networks in terms of technology
UNIT-I: WIRELESS LAN: Infra red vs. radio transmission-Infrastructure and ad-hoc
network-IEEE 802.11-System architecture –Protocol architecture-physical layer-Medium
access control layer-MAC management.
Mobile network layer: Mobile IP -Goals, assumptions and requirements-Entities
and terminology-IP packet delivery-Agent discovery-Registration-Tunneling and
SRNMC Syllabus
encapsulation-optimizations-Reverse tunneling. Mobile ad-hoc networks-Routing -
Overview ad-hoc routing protocols.
UNIT II: UNDERSTANDING CLOUD COMPUTING: Beyond the desktop: An
introduction to Cloud Computing -The pros and Cons of Cloud Computing-Developing
Cloud Services – The Pros and Cons of Cloud service development – Types of Cloud
Service development. Cloud computing for everyone- Cloud Computing for the
community –Cloud Computing for the corporation. Storing and sharing files and other
online content – Understanding cloud storage.
UNIT III: GRID COMPUTING SYSTEMS: Grid Architecture and Service Modeling:
Grid History and Service Families-CPU Scavenging and Virtual Supercomputers-Open
Grid Services Architecture-Data-Intensive Grid Service Models. Grid Application
Trends and Security Measures: Grid Applications and Technology Fusion-Trust
Models for Grid Security Enforcement.
Enabling Technologies for the Internet of Things – Innovative Applications of the
Internet of Things: Applications of the IOT-Retailing and Supply-Chain Management.
Unit IV: SECURITY TRENDS: The OSI Security Architecture-Security Attacks-
Security Services-Security Mechanisms-A Model for Network security. Classical
Encryption Techniques-Symmetric Cipher Model-Substitution Techniques-Transposition
Techniques.
Confidentiality using symmetric encryption: Placement of encryption function-Traffic
confidentiality-Key distribution.
Unit V: KEY MANAGEMENT: Other public-key Cryptosystems- Key management-
Diffie- Hellman Key Exchange. Message authentication and hash functions-
SRNMC Syllabus
Authentication Requirements-Authentication Functions-Message Authentication codes-
Hash functions-Security of hash function and MACs. Digital Signature and
Authentication Protocols-Digital Signature-Authentication Protocols.
Text Books:
1. “Mobile Communications”, Jochen Schiller, Second Edition, Pearson
Publications, 2011. ( Unit I )
2. “Cloud Computing”,Michael Miller,Pearson Education 2014 (Unit II)
3. “Distributed and Cloud Computing”, Kai Hwang, Geoffrey C.Fox, Jack
J.Dongarra and An imprint of Elsevier,2012. (Unit III)
4. “Cryptography and Network Security Principles and Practices”, William
Stallings, Pearson Education, 4th Edition, 2008. (Unit IV & V)
.
Reference Books:
1.”Ad Hoc Wireless Networks: Architecture and Protocols”, C.SivaRam Murthy
and B.S.ManojPrentice Hall, 2004.
2.”Ad Hoc Networks: Technologies and Protocols“, Prasant Mohapatra, Srikanth
and Krishnamurthy, Springer, 2005
3.”Cryptography and Network Security”, Behrouz A.Forouzan, Tata McGraw Hill,
2010.
SRNMC Syllabus
Prepared By:
Signature :
SRI S.RAMASAMY NAIDU MEMORIAL COLLEGE (An Autonomous Institution Re-accredited with „A‟ Grade by NAAC)
SATTUR -626 203.
Department of Computer Science
(For those who are joining in 2015-2016 and after)
Programme : M.Phil (Computer Science) Subject Code :
Semester : II
Part II : Dissertation No. of Credits : 10 Objectives:
To get clear idea about the new concepts in Computer Science / Information
Technology Research fields.
To produce innovative ideas and to develop those ideas into fully-fledged
research results and software and hardware systems.
To provide an opportunity to carry out the research projects with strong analytical
and synthesizing capability with innovative and creative thinking to build a strong
scientific community.
To develop researchers, able to make original scientific contributions that have
SRNMC Syllabus
both practical significance and a rigorous, elegant theoretical background that
underpins various areas in Computer Science and Information Technology.
To develop the ability to apply theoretical and practical tools / techniques to solve
real life problems related to industry, academic institutions and research
laboratories.
To develop the ability of the students to prepare a Dissertation Regulations for the Dissertation
The topic of the dissertation must be recent trends in Computer Science /IT/
Applications selected from reputed National/International Journal or Conference.
The methods and techniques applied in the execution of the work are appropriate
to the subject matter and are original and/or aesthetically effective.
Every scholar is expected to give two seminars one concerning Review of Related
Literature within the four weeks from the beginning of the Second semester and Data
Analysis / Result of the work should be provided before the submission of the final draft
of the dissertation.
The creative work and the dissertation together must make an independent contribution to
existing scholarship in the subject area with which it deals.
All candidates are required to make a presentation of their research findings at the
Department one month prior to Viva-voce examination. The Viva-voce presentation is
regarded as an important part of candidature. The seminar should present the objectives,
methods, findings and significance of the candidate's thesis research.
Candidates are strongly encouraged, where appropriate, to publish work from their
M.Phil research during candidature. However, the preparation of publications should not
impede progress on the thesis, which must remain the candidate's and the supervisor's
priority.
SRNMC Syllabus
A candidate may not include the actual publications such as reprints or journal articles in
their published form as part of the body of the thesis.
The documentation of the work (including catalogue/ program material where
appropriate) is sufficiently thorough and is of a standard that will ensure the work
provides a reference for subsequent researchers.
The students should submit three copies of dissertation with hard binding for evaluation.
The number of pages in the Dissertation may be 100 to 150
The Format of the Dissertation as per the structure given by the Department.
Prepared By:
Signature :
CHAIRMAN DEAN
SRNMC Syllabus