Kumaun University, Nainital, Uttarakhand

M.Sc. COMPUTER SCIENCE

(Choice Based Credit System)
w.e.f. Session 2020-2021
 Core Papers Elective Papers (*) Open Elective Total
Year Semester Credits Credits Credits
Paper Code Title of Paper Paper Code Title of Paper Paper Code Title of Paper Credits
Operating System
MSCS 101
Concepts & Administration
Theoretical foundation of
MSCS 102
Computing
I Advanced Computer 5X4=20 --- ---- ---- ---- ---- ---- 20
MSCS 103
Network
Advanced Database
MSCS 104
First

Management Systems
MSCS L01 LAB: .NET C# & ADBMS
MSCS 201 Compiler Design
Design and Analysis of
MSCS 202
Algorithms
II 5X4=20 --- ---- ---- ---- ---- ---- 20
MSCS 203 Artificial Intelligence
MSCS 204 Software Engineering
MSCS L02 LAB: DAA with JAVA
MSCS 301 Machine Learning Elective I (**)
To be
MSCS 302 (E1-a) Data Mining with Python selected from
MSCS 303 (E1-b) Digital Image Processing (2 papers the list of
As Per the
with OpenCV out of 3) open
Selected
III LAB: Machine Learning 2X4=8 MSCS 304 (E1-c) Cloud Computing electives 1X4=4 20
MSCS L03 Course
with Python/R Elective II (**) 2X4=8 given by
MSCS 302 (E2-a) Internet of Things different
MSCS 303 (E2-b) Network Security and departments
Second

Cryptography
MSCS 304 (E2-c) Cyber Security
MSCS 401 Project Work/Dissertation MSCS 403 (E) Advanced Java To be
MSCS 402 Viva-Voce selected from
MSCS 404 (E) Web Application the list of
Development (2 paper As Per the open
MSCS 405 (E) Mobile App out of 3) Selected electives
IV 2X4=8 1X4=4 20
Development Course given by
2X4=8 different
departments
* Students can choose any one pool of Elective Papers in Semester III either Elective I or Elective II

** Student can choose only 2 subjects out of 3, either from Elective I or Elective II

OE Open electives offered by Department of Computer Science

MSCS 599 (OE) Programming in Python

MSCS 699 (OE) Programming in R

MSCS 799 (OE) Cyber Security Awareness

 MSCS 101: Operating System Concepts & Administration

UNIT I
Introduction: Basics of Operating Systems: Definition – Generations of Operating systems – Types of
Operating Systems, OS Service, System Calls.
Process Management: Processes: Definition, Process Relationship, Process states, Process State transitions,
Process Control Block, Context switching – Threads – Concept of multithreads.
Process Scheduling: Definition, Scheduling objectives, Types of Schedulers, Scheduling criteria: CPU
utilization, Throughput, Turnaround Time, Waiting Time, Response Time (Definition only), Scheduling
algorithms: Pre-emptive and Non, pre-emptive, FCFS – SJF – RR

UNIT II
Inter-process Communication: Race Conditions, Critical Section, Mutual Exclusion, Peterson’s Solution, The
Producer Consumer Problem, Semaphores, Classical IPC Problems: Reader’s & Writer Problem, Dinning
Philosopher Problem etc.
Deadlocks: Definition, Deadlock characteristics, Deadlock Prevention, Deadlock Avoidance: banker’s
algorithm, Deadlock detection and Recovery.

UNIT III
Memory Management: Basic Memory Management: Definition, Logical and Physical address map, Memory
allocation: Contiguous Memory allocation, Fixed and variable partition, Internal and External fragmentation
and Compaction, Paging: Principle of operation, Page allocation, Hardware support for paging, Protection and
sharing, Disadvantages of paging. Virtual Memory: Basics of Virtual Memory, Hardware and control
structures, Locality of reference, Page fault, Working Set, Dirty page/Dirty bit, Demand paging (Concepts
only), Page Replacement policies: Optimal (OPT), First in First Out (FIFO, Least Recently used (LRU).

UNIT IV
I/O Management & Disk Scheduling: I/O Devices and the Organization of I/O Disk I/O, Operating System
Design Issues. File System: File Concept, File Organization and Access Mechanism, File Directories, File
Sharing, Implementation Issues.

UNIT V
Unix Administration: Overview of System Administration – System Administrator Responsibilities, A Brief
History of Unix. User Administration – what is a user, the /etc/passwd file, groups, the /etc/group file,
passwords adding, deleting and modifying user attributes, /etc/profile file, the login process, /etc/motd file,
the wall command. File System Basic - The Hierarchy, files, directories, device files, character and block
devices, the /dev directory, links, symbolick links, a file system tour, df command, du command, find
command. Disk Management – Makin a file system, mkfs command, mount command fstab file, fsck
command, lost+found directory, prtvtoc command. Unix Process – overview, process space, process table,
fork/exec mechanism, ps command, background process, kill command, scheduling jobs, the cron daemon ,
at command, crontab command, cron files. Configuring TCP/IP - /etc/hosts file, ifconfig command.
/etc/services/ file, inetd daemon, /etc/inetd.conf, TCP/IP troubleshooting, the ping and netstat commands.
Network Utilities- Network Services, telnet, ftp, rcp, rlogin, rsh.

Recommended Books:
1. Stalling, Willium, "Operating System", Maxwell Macmillan
2. Silveschatza, Peterson J, "Operating System Concepts", Willey.
3. A Silberschatz, P B. Galvin, G. Gagne, Operating Systems Concepts, 8th Edition, John Wiley Publications.
 MSCS 102: Theoretical foundation of Computing

UNIT I
Introduction to defining language, Kleene closures, Arithmetic expressions, defining grammar, Chomsky
hierarchy, Finite Automata (FA), Transition graph, generalized transition graph.

UNIT II
(Nondeterministic finite Automata (NFA), Deterministic finite Automata (DFA), Construction of DFA from NFA
and optimization, FA with output: Moore machine, Mealy machine and Equivalence, Applications and
Limitation of FA.

UNIT III
Arden Theorem, Pumping Lemma for regular expressions, Myhill-Nerode theorem, Context free grammar:
Ambiguity, Simplification of CFGs, Normal forms for CFGs, Pumping lemma for CFLs, Decidability of CFGs,
Ambiguous to Unambiguous CFG.

UNIT IV
Push Down Automata (PDA): Description and definition, Working of PDA, Acceptance of a string by PDA, PDA
and CFG, Introduction to auxiliary PDA and Two stack PDA.

UNIT V
Turing machines (TM): Basic model, definition and representation, Language acceptance by TM, TM and Type
– 0 grammar, Halting problem of TM, Modifications in TM, Universal TM, Properties of recursive and
recursively enumerable languages, unsolvable decision problem, undecidability of Post correspondence
problem, Church’s Thesis, Recursive function theory

Recommended Books:
1. Hopcroft, Ullman, “Introduction to Automata Theory, Language and Computation”, Nerosa Publishing
House, 3rd Edition
2. K.L.P. Mishra and N.Chandrasekaran, “Theory of Computer Science(Automata, Languages and
Computation)”, PHI, 3rd Edition
 MSCS 103: Advanced Computer Networks

UNIT I
Introduction: Overview of computer network, seven-layer architecture, TCP/IP suite of protocol, etc. Mac
protocols for high-speed LANS, MANs& WIRELESS LANs. (For example, FDDI, DQDB, HIPPI, Gigabit Ethernet,
Wireless Ethernet etc.) Fast access technologies. (For example, ADSL, Cable Modem, etc.)

UNIT II
IPv6: why IPv6, basic protocol, extension & option, support for QoS, security etc., neighbor discovery, auto-
configuration, routing. Change to other protocols. Application programming interface forIPv6. 6bone.

UNIT III
Mobility in network. Mobile. Security related issues. IP Multicasting. Multicasting routing protocols, address
assignments, session discovery, etc. TCP extensions for high-speed networks, transaction- oriented
application, other new options in TCP.

UNIT IV
Network security at various layers. Secure-HTTP, SSL, ESP, Authentication header, Key distribution protocols.
Digital signatures, digital certificates.

UNIT V
Study of complete network architecture of your institution (including topology, network devices cabling
standards, protocol and security features). Hands on experiment for configuring network interface card for
connecting two systems. Test the connectivity between two hosts. Test all options of ping.

Recommended Books:
1. W. R. Stevens,“TCP/IPillustrated,Volume1:The protocols”,Addison Wesley 1994.
2. G.R. Wright. “TCP/IPillustrated, Volume2: The implementation”, Addison Wesley 1995
3. Forouzen, "Data Communication and Networking", TMH
4. W. Stallings, Data and Computer Communication, Macmillan Press
5.
MSCS 104: Advanced Database Management Systems
UNIT I
Introduction: An overview of Database systems, Architecture, Schema and Instances, Data Independence and
Data Base. Entity-Relationship Diagram, generalization, aggregation and association, Data Models:
Hierarchical, Network and Relational.

UNIT II
Relational data model concepts, Integrity constraints, keys, Domain Constraints, Referential Integrity,
Assertions, Triggers, Foreign key, Relational Algebra, Relational Calculus, Tuple and Domain Calculus.
Reduction of Relation Algebra to Relational Calculus, Relation Completeness.

UNIT III
Functional Dependencies, normal forms (1NF, 2NF, 3NF), BCNF, Multivalued Dependencies, 4NF, Join
Dependencies and 5NF. Query processing and optimization. Transaction processing concepts.

UNIT IV
Transaction systems, schedule and recoverability, Testing of serializability, Serializability of schedules, conflicts.
Concurrency control techniques: Locking techniques for concurrency control, Time stamping protocols
validation techniques, multiple granularity, multiversion schemes.

UNIT V
Distributed database: Distributed data storage, data fragmentation, replication and allocation techniques for
distributed database design, recovery in distributed database, protection and security.

Recommended Books:
1. Elmasri, Navathe, “Fundamentals of Database Systems”, Pearson Education.
2. Korth, Silbertz, Sudarshan,” Database Concepts” McGraw Hill
3. C.J. Date, “An Introduction to Database Systems” Addision Wesley
4. Bipin C. Desai,” An Introduction to Database Systems”, Galgotia Publication
5. Mazumdar and Bhattacharya, “Database Management Systems”, TMH
6. Ramakrishnan, Gehrke,” Database Management System”, McGraw Hill.
 MSCS 201: Compiler Design

UNIT I
INTRODUCTION TO COMPILERS: Translators-Compilation and Interpretation-Language processors -The
Phases of Compiler-Errors Encountered in Different Phases-The Grouping of Phases-Compiler Construction
Tools - Programming Language basics

UNIT II
LEXICAL ANALYSIS: Need and Role of Lexical Analyzer-Lexical Errors-Expressing Tokens by Regular
Expressions-Converting Regular Expression to DFA- Minimization of DFA-Language for Specifying Lexical
Analyzers-LEX-Design of Lexical Analyzer for a sample Language.

UNIT III
SYNTAX ANALYSIS: Need and Role of the Parser-Context Free Grammars -Top Down Parsing -General
Strategies-Recursive Descent Parser Predictive Parser-LL (1) Parser-Shift Reduce Parser-LR Parser-LR (0) Item-
Construction of SLR Parsing Table -Introduction to LALR Parser - Error Handling and Recovery in Syntax
Analyzer

UNIT IV
SYNTAX DIRECTED TRANSLATION RUN TIME ENVIRONMENT: syntax directed Definitions-Construction of
Syntax Tree-Bottom-up Evaluation of S-Attribute Definitions- Design of predictive translator - Type Systems-
Specification of a simple type checker-Equivalence of Type Expressions-Type Conversions. RUN-TIME
ENVIRONMENT: Source Language Issues-Storage Organization-Storage Allocation-Parameter Passing-Symbol
Tables-Dynamic Storage Allocation

UNIT V
CODE OPTIMIZATION AND CODE GENERATION: Principal Sources of Optimization-DAG- Optimization of Basic
Blocks-Global Data Flow Analysis-Efficient Data Flow Algorithms-Issues in Design of a Code Generator - A
Simple Code Generator Algorithm

Recommended Books:
1. Aho, Sethi & Ullman, "Compiler Design", Addision Wesley/ Pearson.
2. O. G. Kakde; Compiler Design,4/e; Universities Press (2008)
3. Chattopadhyay Santanu; Compiler Design; Phi Learning (2009)
 MSCS 202: Design and Analysis of Algorithms

UNIT I
Algorithms, Analysis of Algorithm, Design of Algorithms, Time and space complexities, Asymptotic notations,
Growth+ of Functions, Recurrences. Sorting in Polynomial Time: Insertion Sort, Merge Sort, Heap sort and
Quick Sort. Sorting in Linear Time: Counting Sort, Radix Sort, Bucket Sort

UNIT II
Elementary Data Structure: Stacks, Queues, Linked List, Binary Search Tree, Hash Table, Red Black Trees, AVL
Tree, Splay Tree, Augmenting Data Structure Advanced Data Structure: Binomial Heap, B-tree, Fibonacci
Heap, and Data Structure for Disjoint sets.

UNIT III
Advanced Design and Analysis Techniques: Dynamic Programming, Greedy Algorithm, Backtracking, Branch-
and- Bound. Huffman Coding.

UNIT IV
Graph Algorithms: Elementary Graph Algorithm, Breadth First Search, Depth First Search, Minimum Spanning
Tree, Kruskal’s Algorithm, Prim’s Algorithm, Single Source Shortest Path, All Pair Shortest Path, Maximum
Flow and Travelling Salesman Problem.

UNIT V
Randomized Algorithm: String Matching, NP-Hard and NP- Completeness, Approximation Algorithms.

Recommended Books:
1. Horowitz Sahni, “Fundamentals of Computer Algorithm”, Galgotia,
2. Coreman Leiserson etal, “Introduction to Algorithm”, PHI
3. Brassard Bratley, “Fundamental of Algorithm”, PHI
4. M.T. Goodrich etal, “Algorithms Design”, John Wiley and Sons
5. A V. Aho etal, “The Design and Analysis of Algorithms”, Pearson Education
 MSCS 203: Artificial Intelligence

UNIT I
Early work in AI, AI and related fields, Problem Solving Introduction, State space search, Production system,
Breadth First Search, Depth First Search, Problem Characteristics, Heuristic Search-Generate and Test, Simple
Hill climbing, Path Finding Algorithm

UNIT II
Knowledge representation, Definition and Importance of Knowledge, Knowledge based system,
Representation of knowledge, Introduction of predicate logic, Well-formed formula, Interference rule and
numerical, The Resolution principle, Representation using rule.

UNIT III
Natural Language Processing: Introduction, Problems in Natural Language Understanding, Overview of
Linguistics, Grammars and Languages, Natural Language Generation, Natural Language Systems, Top-Down
Parser, Bag of Words Model.

UNIT IV
Evolutionary Computation, Genetic Algorithms, Terminologies and Operators of GA, Ant Colony Optimization,
Particle Swarm Optimization, GA Tool using MATLAB.

UNIT V
Introduction, Need and Justification of Expert System, Knowledge Acquisition, Knowledge System building
tools, Basic steps of Expert System Development,
Fuzzy Sets, Operations on Fuzzy Sets, Fuzzy Relations, Membership Functions, Fuzzy Rules and Fuzzy
Reasoning, Fuzzy Inference Systems, Fuzzy Decision Making

Recommended Books:
1. Elian Rich and Kelvin Knight, “AI”, TMH
2. Dan W. Patterson, “Introduction to Artificial Intelligence and Expert Systems”
3. K M FU,” Neural Network in Computer Intelligence”, Mc Graw Hill
4. Russel and Norvig, “AI: A modern approach”, Pearson Education
 MSCS 204: Software Engineering

UNIT I
Introduction: Software Engineering vs. Traditional Programming, System Development Life Cycle (Software
Production Process, Conception, Initiation, Analysis Design, Construction, Testing, Implementation). Waterfall
Model, Evolutionary Model. Factors affecting Software Development and Maintenance.

UNIT II
Software Project Management: Defining the Problem, developing a Solution Strategy, Planning the
Development Process, Measurement of Software Productivity and Quality.

UNIT III
Software Engineering Principles &Tools: Tools of Design (Data Flow Diagrams, Data Dictionary, Decision
Tree, Decision Tables), Modularization (Coupling)

UNIT IV
Testing: Testing fundamentals, Unit testing, Blackbox testing, Whitebox testing, Basic Path testing, Control
Structure testing, Integration testing.

UNIT V
Software maintenance: Introduction to Software Maintenance, Enhancing Maintainability During
Development (analysis Activities, Standards and Guidelines, Design activities, Implementation Activities,
Supporting Documents) Managerial Aspects of Software Maintenance (Change Control Board, Change
Request summaries, Quality Assurance Activities, Organizing Maintenance Programs).

Recommended Books:
1. R.F.Fairley,, “Software Engineering Concepts”, McGraw Hill.
2. R.S.Press Man , “Software Engineering A Practitioners Approach” McGraw Hill.
3. Rajib Mall, “Fundamentals of Software Engineering”. PHI.
4. Pankaj Jalote. “An Integrated Approach to Software Engineering”, Narosa
 MSCS 301: Machine Learning

UNIT I
Introduction: Machine Learning Definitions, Application of Machine Learning, Problems, Data and Tools,
Python for Machine Learning, Data Pre-processing in Python

UNIT II
Regression: Linear Regression-Simple, Multiple, Polynomial Regression, Support Vector Regression,
Regression Trees, Evaluating Regression Models Performance

UNIT III
Classification: Logistic Regression, K-Nearest Neighbors (K-NN), SVM, Naïve Bayes, Decision tree and Random
Forest

UNIT IV
Convolution Neural Networks: What is Convolutional Neural Network, Foundation of Convolutional Neural
Network, ResNet Case Study, Object Detection, Application: Face Recognition and Style Transfer

UNIT V
Neuro - Fuzzy Modeling: Adaptive Neuro-Fuzzy Inference Systems, Coactive Neuro-Fuzzy Modeling, Rule
base Structure Identification, ANFIS Applications using MATLAB.

Recommended Books:
1. Machine Learning Algorithms by Giuseppe Bonaccorso
2. Hands-on Machine Learning with Scikit-Learn, Keras& TensorFlow
3. Make Your Own Neural Network by Tariq Rashid
4. Neural Networks Math A Visual Introduction for Beginners by Michael Taylor
 MSCS 302 (E1-a): Data Mining with Python
Unit I
DSS-uses, Definition, Operational Database, Introduction to DATA Warehousing, Data-Mart, Concept of Data-
Warehousing, Multidimensional Database Structures. Client/server computing model & Data Warehousing.
Parallel Processors & cluster Systems. Distributed DBMS implementations.

Unit II
Data warehousing. Data Warehousing components. Building a Data Warehouse. Warehouse Database
Mapping the Data Warehouse to Multiprocessor Architecture. DBMS Schemas for Decision Support. Data
Extraction, Clean-up & Transformation Tools. Metadata.

Unit III
Business Analysis. Reporting & Query Tools & Applications. Online Analytical Processing (OLAP). Patterns &
Models. Statistics. Artificial Intelligence.

Unit IV
A brief introduction to python language, literals, functions, operators, anonymous functions. Introduction to
Python packages for data science-NumPy, pandas, Keras and cubes.

Unit- V
Knowledge Discovery, Data Mining. Introduction to Data-Mining. Techniques of Data-Mining. Decision Trees.
Neural Networks. Nearest Neighbour. & clustering. Genetic Algorithms., Implementation of these techniques
in Python.

Recommended Books:
1. Introduction to Data Mining Tan, Steinbach, & Kumar Pearson-Addison Wesley 2006
2. Data Mining: Practical Machine Learning and Techiniques (2nd eds) Witten & Frank Elsevier 2005
3. Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management (2nd eds) Berry &
Linoff Wiley 2004
4. Pattern Recognition & Machine Learning Bishop Springer 2007
5. Data Mining and Data Warehousing: Principles and Practical Techniques
6. Mastering Data Mining with Python - Find patterns hidden in your data
7. Data Science Using Python and R
 MSCS 303 (E1-b): Digital Image Processing with OpenCV
Unit I
Introduction: Digital Image Processing System, Image Perception, Colour Representation, Image Acquisition,
Image Digitization, Image model, Image scanning techniques, Noise, Image Processors, A brief overview of
OpenCV, Installing OpenCV in Windows, Linux, how are Image formed and stored.

Unit II
Statistical Operation: Gray Level Transformation, Histogram Processing, Grey Level Transformation
Techniques, Multi Image Operations, OpenCV-Gray scaling, histogram representation of images, drawing over
images, Transformation, Scaling, Cropping, Darkening/Brightening Images, Masking Blurring and Sharpening.

Unit III
Segmentation and Edge Detection: Segmentation, Region Based Segmentation, Thresholding, Basic Edge
Detection, Colour Edge Detection, Pyramid Edge Detection, OpenCV – Edge Detection using Image Gradient,
Segmentation and Contours, Link Detection, Circle Detection and Blob Detection.

Unit IV
Object Recognition: System Component, Complexity of Object Recognition, Object Representation, Feature
Detection, Recognition Strategies. OpenCV-Finding Corners, Extracting Features, Face Detection using HAAR’s
Cascade.

Unit V
Image Compressions: Introduction to Image compression, Basic Requirements, Different Types of
Compressions, Coding algorithms: Run Length Coding, Huffman Coding LZW, JPEG

Recommended Books:
1. S. Nagabhushana, “Computer Vision and Image Processing”, New Age International Publishers.
2. Rosenfield, “Digital Picture Processing”, KAK Academic Press Orlando
3. Gonzalez and Wintz, “Digital Image Processing”, Addison Wesley
 MSCS 304 (E1-c): Cloud Computing
UNIT I
Cloud Computing Overview, Recent trends in Computing, Grid Computing, Cluster Computing, Distributed
Computing, Utility Computing, Cloud Computing,

UNIT II
Introduction to Cloud Computing, History of Cloud Computing, Cloud service providers, Benefits and
limitations of Cloud Computing,

UNIT III
Cloud Computing Architecture, Comparison with traditional computing architecture (client/server), Services
provided at various levels, Service Models- Infrastructure as a Service (IaaS), Platform as a Service (PaaS),
Software as a Service (SaaS), How Cloud Computing Works, Deployment Models- Public cloud, Private cloud,
Hybrid cloud, Community cloud, Case study of NIST architecture.

UNIT IV
Service Management in Cloud Computing, Service Level Agreements (SLAs), Billing & Accounting, Comparing
Scaling Hardware: Traditional vs. Cloud, Economics of scaling.

UNIT V
Cloud Security: Infrastructure Security- Network level security, Host level security, Application level security,
Data security and Storage- Data privacy and security Issues, Jurisdictional issues raised by Data location,
Authentication in cloud computing.

Recommended Books:
1. Cloud Computing Bible, Barrie Sosinsky, Wiley-India, 2010
2. Cloud Security: A Comprehensive Guide to Secure Cloud Computing, Ronald L. Krutz, Russell Dean Vines,
Wiley-India, 2010
3. Gautam Shroff, Enterprise Cloud Computing Technology Architecture Applications, Adobe Reader ebooks
available from eBooks.com,2010
4. Toby Velte, Anthony Velte, Robert Elsenpeter, Cloud Computing, A Practical Approach, McGraw Hills,
2010.
5. Dimitris N. Chorafas, Cloud Computing Strategies, CRC Press, 2010.
 MSCS 302 (E2-a): Internet of Things
UNIT I
OVERVIEW: IoT-An Architectural Overview– Building an architecture, Main design principles and needed
capabilities, An IoT architecture outline, standards considerations. M2M and IoT Technology Fundamentals-
Devices and gateways, Local and wide area networking

UNIT II
REFERENCE ARCHITECTURE: Reference Model and architecture, IoT reference Model - IoT Reference
Architecture- Introduction, Functional View, Information View, Deployment and Operational View, Other
Relevant architectural views. Real-World Design Constraints- Introduction, Technical Design constraints-
hardware is popular again, Data representation and visualization, Interaction and remote control.

UNIT III
IOT DATA LINK LAYER & NETWORK LAYER PROTOCOLS: PHY/MAC Layer (3GPP MTC, IEEE 802.11, IEEE
802.15), Wireless HART, Z Wave, Bluetooth Low Energy, Zigbee Smart Energy, DASH7 - Network Layer-IPv4,
IPv6, 6LoWPAN, 6TiSCH, ND, DHCP, ICMP, RPL, CORPL, CARP

UNIT IV
TRANSPORT & SESSION LAYER PROTOCOLS: Transport Layer (TCP, MPTCP, UDP, DCCP, SCTP)- (TLS, DTLS) –
Session Layer HTTP, CoAP, XMPP, AMQP, MQTT

UNIT V
SERVICE LAYER PROTOCOLS & SECURITY: Service Layer -oneM2M, ETSI M2M, OMA, BBF – Security in IoT
Protocols – MAC 802.15.4, 6LoWPAN, RPL, Application Layer

Recommended Books:
1. Jan Holler, VlasiosTsiatsis, Catherine Mulligan, Stefan Avesand, StamatisKarnouskos, David Boyle, “From
Machine-to-Machine to the Internet of Things: Introduction to a New Age of Intelligence”, 1st Edition,
Academic Press, 2014.
2. Peter Waher, “Learning Internet of Things”, PACKT publishing, BIRMINGHAM – MUMBAI
3. Vijay Madisetti and ArshdeepBahga, “Internet of Things (A Hands-onApproach)”, 1 st Edition, VPT, 2014.
 MSCS 303 (E2-b): Network Security and Cryptography
Unit I
An illustrative communication game – safeguard versus attack – Probability and Information Theory -
Algebraic foundations – Number theory.

Unit II
Substitution Ciphers – Transposition Ciphers – Classical Ciphers – DES – AES – Confidentiality Modes of
Operation – Key Channel Establishment for symmetric cryptosystems.

Unit III
Diffie-Hellman Key Exchange protocol – Discrete logarithm problem – RSA cryptosystems & cryptanalysis –
ElGamal cryptosystem – Need for stronger Security Notions for Public key Cryptosystems – Combination of
Asymmetric and Symmetric Cryptography – Key Channel Establishment for Public key Cryptosystems - Data
Integrity techniques – Symmetric techniques - Asymmetric techniques

Unit IV
Authentication Protocols Principles – Authentication protocols for Internet Security – SSH Remote logic
protocol – Kerberos Protocol – SSL & TLS – Authentication frame for public key Cryptography – Directory
Based Authentication framework – Non - Directory Based Public-Key Authentication framework.

Unit V
Protecting Programs and Data – Information and the Law – Rights of Employees and Employers – Software
Failures – Computer Crime – Privacy – Ethical Issues in Computer Security.

Recommended Books:
1. William Stallings, “Cryptography and Network Security: Principles and Practice“, PHI
2. A. Johannes Buchmann, “Introduction to Cryptography”, Sringer- Verlag
3. Atul Kahate, “Cryptography and Network Security”
4. Cryptography and Network Security by Forouzan
 MSCS 304 (E2-c): Cyber Security

Unit I
Introduction to Cyber Security: Overview of Cyber Security, Internet Governance – Challenges and
Constraints, Cyber Threats: - Cyber Warfare-Cyber Crime-Cyber Terrorism-Cyber Espionage, need for a
Comprehensive Cyber Security Policy, need for a Nodal Authority, Need for an International convention on
Cyberspace.

Unit II
Cyber Security Vulnerabilities and Cyber Security Safeguards: Cyber Security Vulnerabilities-Overview,
vulnerabilities in software, System administration, Complex Network Architectures, Open Access to
Organizational Data, Weak Authentication, Unprotected Broadband communications, Poor Cyber Security
Awareness. Cyber Security Safeguards- Overview, Access control, Audit, Authentication, Biometrics,
Cryptography, Deception, Denial of Service Filters, Ethical Hacking, Firewalls, Intrusion Detection Systems,
Response, Scanning, Security policy, Threat Management.

Unit III
Securing Web Application, Services and Servers: Introduction, Basic security for HTTP Applications and
Services, Basic Security for SOAP Services, Identity Management and Web Services, Authorization Patterns,
Security Considerations, Challenges.

Unit IV
Intrusion Detection and Prevention: Intrusion, Physical Theft, Abuse of Privileges, Unauthorized Access
by Outsider, Malware infection, Intrusion detection and Prevention Techniques, Anti-Malware software,
Network based Intrusion Detection Systems, Network based Intrusion Prevention Systems, Host based
Intrusion Prevention Systems, Security Information Management, Network Session Analysis, System Integrity
Validation.

Unit V
Cryptography and Network Security: Introduction to Cryptography, Symmetric key Cryptography,
Asymmetric key Cryptography, Message Authentication, Digital Signatures, Applications of Cryptography.
Overview of Firewalls- Types of Firewalls, User Management, VPN Security, Security Protocols: - security at
the Application Layer- PGP and S/MIME, Security at Transport Layer- SSL and TLS, Security at Network Layer-
IPsec.

Recommended Books:
1. Cyber Security by Nina Godbole Sunit Belapure
2. Cybersecurity - Attack and Defense Strategies: Infrastructure security with Red Team and Blue Team
tactics by Yuri Diogenes
3. Cryptography and Network Security by Forouzan
4. The Web Application Hacker's Handbook: Finding and Exploiting Security Flaws by Dafydd Stuttard
 MSCS 403(E): Advance Java
UNIT I
Revising the Basics: Java Environment, Basic Language Elements-Lexical Tokens, Identifiers, Keywords,
Literals, Comments, Primitive Datatypes, Operators Assignments, OOPs Concepts-Class and Interfaces,
Fundamental, Object Lifetime and Garbage Collection, Constructors, Access Control, Overloading, “this”
reference, Inheritance.

UNIT II
Java Advanced: Packages – Organizing Classes and Interfaces in Packages, Defining Packages, CLASSPATH
Setting for Packages, Making JAR Files for Library Packages Import, Array and String, Exception Handling,
Multithreading, Collection Framework.

UNIT III
Java Server Technologies: Web Application Basics, Architecture and challenges of Web Application,
Introduction to servlet, Servlet life cycle, Developing and Deploying Servlets, Exploring Deployment,
Descriptor, Handling Request and Response.

UNIT IV
Java Serve Pages: Basics of JSP-JSP API, JSP in IDE’s, Scripting elements, 9 Implicit Objects, Directive
Elements, Action Elements.

UNIT V
Overview of Mail Protocols-SMTP, POP3, IMAP, Sending Mail, sending email through Gmail Server,
Receiving Email, Sending HTML content.

Recommended Books:
1. Murachs Java Servlets & JSP (Murach: Training & Reference)
2. Head First Servlets & JSP: Passing the Sun Certified Web Component Developer Exam
3. Web Development with Java: Using Hibernate, JSPs and Servlets Kindle Edition
 MSCS 404(E): Web Application Development

UNIT I
Introduction to HTML: Basics of HTML, formatting and fonts, commenting code, hyperlink, lists, tables,
images, forms, Meta tags, Character entities, frames and frame sets, Overview and features of HTML5.

UNIT II
Style Sheets: Need for CSS, Introduction to CSS, basic syntax and structure, using CSS, background images,
colours and properties, manipulating texts, using fonts, borders and boxes, margins, padding lists, positioning
using CSS, CSS2, Overview and features of CSS3

UNIT III
Introduction to JavaScript: JavaScript Variables and Data Types, Declaring Variables, Data Types, Statements
and Operators, Control Structures, Conditional Statements, Loop Statements, Object-Based Programming,
Functions, Executing Deferred Scripts, Objects, Message box in JavaScript, Dialog Boxes, Alert Boxes, Confirm
Boxes, Prompt Boxes, JavaScript with HTML, Events, Event Handlers, Forms, Forms Array.

UNIT IV
Node JS: Introduction to Node JS, Setup Development Environment, Node JS Modules, Node Package
Manager, Creating Web Server, File System, Debugging Node JS Application, Events, Express JS, Serving Static
Resources

UNIT V
Node JS Database Connectivity: Connecting String, Configuring, working with Select Command, Updating
Records, Deleting Records.

Recommended Books:
1. Jeffrey C. Jackson, “Web Technologies: A Computer Science Perspective”, Prentice Hall, 2007
2. JavaScript: The Good Parts by Douglas Crockford
3. HTML5 for Web Designers by Jeremy Keith
4. The Art and Science of CSS: Create Inspirational, Standards-Based Web Designs by Cameron Adams
5. Beginning Node.js by Basarat Ali Syed
6. Getting MEAN with Mongo, Express, Angular, and Node by Simon Holmes
 MSCS 405(E): Mobile App Development

UNIT I
Android Architecture Overview: The Android Software Stack, The Linux Kernel, Android Runtime - Dalvik
Virtual Machine, Android Runtime – Core Libraries, Dalvik VM Specific Libraries, Java Interoperability
Libraries, Android Libraries, Application Framework.

UNIT II
Introduction to Android Studio: Introduction, Installation, Tour of Android Studio, Designer Features –
Button, Text Fields, Messages. Running an Emulator, running on a Physical Android Device, Debugging.

UNIT III
Media: Images, Video and Sound: Layout, Animations, Video, Audio- Controlling Audio, Audio Volume
Seeking, Grid Layout, WebView, List View.

UNIT IV
Advanced Android Features: Downloading Web Content, Downloading Images, Parsing JSON Data, Maps and
Geolocation, Permanent Storage, SQLite.

UNIT V
A Popular Social Media App Clone: Clone of Any one of the popular social media app: Like Twitter, Instagram,
Snapchat.

Recommended Books:
1. Android App Development All-in-One for Dummies, 3ed
2. Android Application Development, Black Book
3. Android Studio IDE Quick Reference
 MSCS 599 (OE): Programming in Python

Unit I
Introduction to Python: An introduction to the Python programming language. Covers details of how to start
and stop the interpreter and write programs. Introduces Python's basic data types, files, functions, and error
handling. Working with Data: A detailed tour of how to represent and work with data in Python. Covers tuples,
lists, dictionaries, and sets

Unit II
Program Organization and Functions: More information about how to organize larger programs into
functions. A major focus of this section is on how to design functions that are reliable and can be easily reused
in other settings. Also covers technical details of functions including scoping rules, documentation strings, and
anonymous functions.

Unit III
Classes and Objects: An introduction to object-oriented programming in Python. Describes how to create new
objects, overload operators, and utilize Python special methods. Also covers basic principles of object-oriented
programming including inheritance and composition.

Unit IV
Iterators and Generators: Covers the iteration protocol, Iterable objects, generators and generator
expressions. A major focus of this section concerns the use of generators to set up data processing pipelines--a
particularly effective technique for addressing a wide variety of common systems programming problems (e.g.,
processing large data files, handling infinite data streams, etc.).

Unit V
Testing and Debugging: This section discusses many issues related to Python software development. This
includes effective use of program testing using both the doc test and unit test modules, and effective use of
assertions. The Python debugger and profiler are also described.

Recommended Books:
1. Python the Complete Reference, Martin C. Brown
2. Learn Python 3 The Hard Way, Zed A. Shaw
3. Python Essential Reference, David M. Beazley
 MSCS 699 (OE): Programming in R

UNIT I
Overview of R, Installing R in windows and Linux, R Basics – Math, Variables and Strings.

UNIT II
Vectors and Factors, Vector Operation, Arrays & Matrices, Lists, Data frames, Working with Data frames.

UNIT III
Control Structures, Functions, Scoping Rules, Dates and Times, Loop Functions, Object and Classes
Debugging tools.

UNIT IV
Reading CSV and Excel Files, reading text files, Writing and Saving data objects to file in R, String Operations
in R, Regular Expressions, Dates in R.

UNIT V
Brief overview of Data Science with R, Regression-Simple, Logistics, Polynomial. Classification-K-Nearest
Neighbor, Decision Tree.

Recommended Books:
1. R Programming for dummies
2. R in action
3. Beginning R: The Statistical Programming Language
4. Practical Data Science with R (MANNING)
 MSCS 799 (OE): Cyber Security Awareness

Unit I
Basic of computer and Cyber Security-History of Computers, Areas of Application, Computers and its
components, Application Software and System Software, Introduction to Operating System

UNIT II
Basics of Networks and internet, Types of Network, Definition of Cyber Security, Search Engines, E –mails
and WWW, Internetworking Devices, Internet Service provider, IP Address, Working of Email system,
Domain Name System, Peer to peer sharing.

UNIT III
Overview of Security threats, Hacking Techniques-Password cracking, Insecure Network connections,
Malicious code, Concept of Fire wall Security, Email security- web authentication

UNIT IV
Information Technology Law (Cyber Law), Evolution of the IT Act, Genesis and Necessity, Salient features of
the IT Act, 2000, various authorities under IT Act and their powers, Penalties & Offences.

UNIT V
Sensitive Personal Data or Information (SPDI) in Cyber Law, SPDI Definition and Reasonable Security
Practices in India, Reasonable Security Practices – International perspective, Cloud Computing & Law.

Recommended Books:
1. Cyber Security by Nina Godbole Sunit Belapure
2. Cybersecurity - Attack and Defense Strategies: Infrastructure security with Red Team and Blue Team
tactics by Yuri Diogenes
3. Cryptography and Network Security by Forouzan
4. The Web Application Hacker's Handbook: Finding and Exploiting Security Flaws by Dafydd Stuttard