Abhi PYQ

6th Semester Syllabus

CSE (Cyber Security)

Credits Table

Course Title L T P Credits
Machine Learning [152601] 3 1 0 4
Cryptography [152602] 3 0 0 3
Web application Security [152603] 3 0 0 3
AI and Ethics [152604] 1 0 0 1
Constitution of India [152605] 3 0 0 0
Program Elective Course-II [1526XX] 3 0 0 3
Program Elective Course-III [1526XX] 3 0 0 3
Machine Learning Lab [152601P] 0 0 4 2
Web application Security Lab [152603P] 0 0 4 2
NPTEL Course-II Lab [152606P] 0 0 4 2
TOTAL 23

Theory Subjects

Lab Subjects

Machine Learning [152601]

  • Unit-1.0: Introduction
    • Basic definitions
    • Linear Algebra
    • Statistical learning theory
    • Types of learning
    • Hypothesis space and Inductive bias
    • Evaluation and cross validation
    • Optimization
  • Unit-2.0: Statistical Decision Theory
    • Statistical Decision Theory
    • Bayesian Learning (ML, MAP, Bayes estimates, Conjugate priors)
    • Linear Regression
    • Ridge Regression
    • Lasso
    • Principal Component Analysis
    • Partial Least Squares
  • Unit-3.0: Linear Classification
    • Linear Classification
    • Logistic Regression
    • Linear Discriminant Analysis
    • Quadratic Discriminant Analysis
    • Perceptron
    • Support Vector Machines + Kernels
    • Artificial Neural Networks + Back Propagation
    • Decision Trees
    • Bayes Optimal Classifier
    • Naive Bayes
  • Unit-4.0: Hypothesis testing
    • Hypothesis testing
    • Ensemble Methods
    • Bagging
    • Adaboost
    • Gradient Boosting
  • Unit-5.0: Clustering
    • Clustering
    • K-means
    • K-medoids
    • Density-based Hierarchical
    • Spectral
  • Unit-6.0: Expectation Maximization
    • Expectation Maximization
    • GMMs
    • Learning theory
    • Intro to Reinforcement Learning
    • Bayesian Networks

Text/Reference Books:

  1. Machine Learning. Tom Mitchell. First Edition, McGraw-Hill, 1997
  2. Introduction to Machine Learning Edition 2, by Ethem Alpaydin.
  3. J. Shavlik and T. Dietterich (Ed), Readings in Machine Learning, Morgan Kaufmann, 1990.
  4. P. Langley, Elements of Machine Learning, Morgan Kaufmann, 1995.
  5. Understanding Machine Learning. Shai Shalev-Shwartz and Shai Ben-David. Cambridge University Press. 2017. [SS-2017]
  6. The Elements of Statistical Learning. Trevor Hastie, Robert Tibshirani and Jerome Friedman. Second Edition. 2009. [TH-2009]

Cryptography [152602]

  • Unit-1.0: Attacks on Computers and Computer Security
    • Introduction
    • The need for security
    • Security approaches
    • Principles of security
    • Types of Security attacks
    • Security services
    • Security Mechanisms
    • A model for Network Security Cryptography: Concepts and Techniques: Introduction
    • Plain text and cipher text
    • Substitution techniques
    • Transposition techniques
    • Encryption and decryption
    • Symmetric and asymmetric key cryptography
    • Steganography
    • Key range and key size
    • Possible types of attacks
  • Unit-2.0: Symmetric key Ciphers
    • Block Cipher principles & Algorithms (DES, AES)
    • Block cipher modes of operation
    • Stream ciphers
    • RC4
    • Location and placement of encryption function
    • Key distribution
  • Unit-3.0: Asymmetric key Ciphers
    • Principles of public key cryptosystems
    • Algorithms (RSA, Diffie-Hellman)
    • Key Distribution
  • Unit-4.0: Message Authentication Algorithms and Hash Functions
    • Authentication requirements
    • Functions
    • Message authentication codes
    • Hash Functions
    • Secure hash algorithm
    • Whirlpool
    • HMAC
    • Digital Signatures
    • Authentication Applications: Kerberos
    • X.509
    • Authentication Service
    • Public Key Infrastructure
    • Biometric Authentication
  • Unit-5.0: E-Mail Security
    • Pretty Good Privacy
    • S/MIME
    • IP Security: IP Security overview
    • IP Security architecture
    • Authentication Header
    • Encapsulating security payload
    • Combining security associations
    • Key management
  • Unit-6.0: Web Security
    • Web security considerations
    • Secure Socket Layer and Transport Layer Security
    • Secure electronic transaction
    • Intruders
    • Virus and Firewalls: Intruders
    • Intrusion detection
    • Password management
    • Virus and related threats
    • Countermeasures
    • Firewall design principles
    • Types of firewalls
    • Case Studies on Cryptography and security: Secure Inter-branch Payment Transactions
    • Cross site Scripting Vulnerability
    • Virtual Elections

Text/Reference Books:

  1. Cryptography and Network Security: William Stallings, Pearson Education, 4th Edition
  2. Cryptography and Network Security: Atul Kahate, Mc Graw Hill, 2nd Edition.
  3. Cryptography and Network Security: C K Shyamala, N Harini, Dr T R Padmanabhan, Wiley India, 1st Edition.
  4. Cryptography and Network Security: Forouzan Mukhopadhyay, Mc Graw Hill, 2nd Edition
  5. Information Security, Principles and Practice: Mark Stamp, Wiley India.
  6. Principles of Computer Security: WM.Arthur Conklin, Greg White, TMH
  7. Introduction to Network Security: Neal Krawetz, CENGAGE Learning
  8. Network Security and Cryptography: Bernard Menezes, CENGAGE Learning

Web Application Security [152603]

  • Unit-1.0: Fundamentals of Web Application Security
    • The history of Software Security-Recognizing Web Application Security Threats
    • Web Application Security
    • Authentication and Authorization
    • Secure Socket layer
    • Transport layer Security
    • Session Management-Input Validation
  • Unit-2.0: Secure Development and Deployment
    • Web Applications Security - Security Testing
    • Security Incident Response Planning
    • The Microsoft Security Development Lifecycle (SDL)
    • OWASP Comprehensive Lightweight Application Security Process (CLASP)
    • The Software Assurance Maturity Model (SAMM)
  • Unit-3.0: Secure API Development
    • API Security- Session Cookies
    • Token Based Authentication
    • Securing Natter APIs: Addressing threats with Security Controls
    • Rate Limiting for Availability
    • Encryption
    • Audit logging
    • Securing service-to-service APIs: API Keys
    • OAuth2
    • Securing Microservice APIs: Service Mesh
    • Locking Down Network Connections
    • Securing Incoming Requests
  • Unit-4.0: Vulnerability Assessment and Penetration Testing
    • Vulnerability Assessment Lifecycle
    • Vulnerability Assessment Tools: Cloud-based vulnerability scanners
    • Host-based vulnerability scanners
    • Network-based vulnerability scanners
    • Database-based vulnerability scanners
    • Types of Penetration Tests: External Testing
    • Web Application Testing
    • Internal Penetration Testing
    • SSID or Wireless Testing
    • Mobile Application Testing
  • Unit-5.0: Hacking Techniques and Tools
    • Social Engineering
    • Injection
    • Cross-Site Scripting (XSS)
    • Broken Authentication and Session Management
    • Cross-Site Request Forgery
    • Security Misconfiguration
    • Insecure Cryptographic Storage
  • Unit-6.0: Failure to Restrict URL Access, Tools
    • Comodo
    • OpenVAS
    • Nexpose
    • Nikto
    • Burp Suite
    • Etc.

Text/Reference Books:

  1. Andrew Hoffman, Web Application Security: Exploitation and Countermeasures for Modern Web Applications, First Edition, 2020, O'Reilly Media, Inc.

AI and Ethics [152604]

  • Unit-1.0: Introduction
    • Definition of morality and ethics in AI
    • AI
    • And society
  • Unit-2.0: Impact of AI
    • Impact on society
    • Impact on human psychology
    • Impact on the legal system
    • Impact on the environment and the planet
    • And Impact on trust
  • Unit-3.0: Ethical Initiatives in AI
    • International ethical initiatives
    • Ethical harms
    • And concerns
    • Case study: healthcare robots
    • Autonomous Vehicles
    • Warfare
    • And weaponization
  • Unit-4.0: AI Standards And Regulation
    • Model Process for Addressing Ethical Concerns During System Design
    • Transparency of Autonomous Systems
    • Data Privacy Process
    • Algorithmic Bias Considerations
    • Ontological Standard for Ethically Driven Robotics and Automation Systems
  • Unit-5.0: Rob ethics: Social and Ethical Implication of Robotics
    • Robotics- Ethics and Morality
    • Moral Theories-Ethics in Science and Technology
    • Ethical Issues in an ICT Society
    • Harmonization of Principles
    • Ethics and Professional Responsibility
    • Robotics Taxonomy
  • Unit-6.0: Challenges and Opportunities
    • Ethical issues in artificial intelligence
    • Societal Issues Concerning the Application of Artificial Intelligence in Medicine
    • Decision-making role in industries
    • And National and International Strategies on AI

Text/Reference Books:

  1. Eleanor Bird, Jasmin Fox-Skelly, Nicola Jenner, Ruth Larbey, Emma Weitkamp and Alan Winfield," The ethics of artificial intelligence: Issues and initiatives", EPRS | European Parliamentary Research Service Scientific Foresight Unit (STOA) PE 634.452- March 2020.
  2. Patrick Lin, Keith Abney, George A Bekey," Robot Ethics: The Ethical and Social Implications of Robotics", The MIT Press- January 2014.
  3. Towards a Code of Ethics for Artificial Intelligence (Artificial Intelligence: Foundations, Theory, and Algorithms) by Paula Boddington, November 2017.
  4. Mark Coeckelbergh," AI Ethics", The MIT Press Essential Knowledge series, April 2020.

Constitution of India [152605]

  • Unit-1.0: Meaning of the constitution law and constitutionalism
    • Meaning of the constitution law and constitutionalism
    • Historical perspective of the Constitution of India
    • Salient features and characteristics of the Constitution of India
  • Unit-2.0: Scheme of the fundamental rights
    • Scheme of the fundamental rights
    • The scheme of the Fundamental Duties and its legal status
    • The Directive Principles of State Policy - Its importance and implementation
  • Unit-3.0: Federal structure and distribution of legislative and financial powers
    • Federal structure and distribution of legislative and financial powers between the Union and the States
    • Parliamentary Form of Government in India - The constitution powers and status of the President of India
  • Unit-4.0: Amendment of the Constitutional Powers and Procedure
    • Amendment of the Constitutional Powers and Procedure
    • The historical perspectives of the constitutional amendments in India
  • Unit-5.0: Emergency Provisions
    • Emergency Provisions: National Emergency
    • President Rule
    • Financial Emergency
    • Local Self Government - Constitutional Scheme in India
  • Unit-6.0: Scheme of the Fundamental Right to Equality
    • Scheme of the Fundamental Right to Equality
    • Scheme of the Fundamental Right to certain Freedom under Article 19
    • Scope of the Right to Life and Personal Liberty under Article 21

Text/Reference Books:

  1. "Constitution of India" (for Competitive Exams) Published by Naidhruva Edutech Learning Solutions, Bengaluru. - 2022.
  2. "Introduction to the Constitution of India", (Students Edition.) by Durga Das Basu (DD Basu): Prentice-Hall, 2008.
  3. "Constitution of India, Professional Ethics and Human Rights" by Shubham Singles, Charles E. Haries, and et al: published by Cengage Learning India, Latest Edition - 2019.
  4. "The Constitution of India" by Merunandan K B: published by Merugu Publication, Second Edition, Bengaluru.
  5. "Samvidhana Odu" - for Students & Youths by Justice HN Nagamohan Dhas, Sahayana, kerekon.
  6. M.Govindarajan, S.Natarajan, V.S.Senthilkumar, "Engineering Ethics", Prentice-Hall, 2004.

Program Elective Course-II: Soft Computing [152607]

  • Unit-1.0: Introduction to Soft Computing
    • Evolution of Computing: Soft Computing Constituents
    • Soft vs Hard Computing
    • From Conventional AI to Computational Intelligence: Machine Learning Basics
  • Unit-2.0: Neural Networks
    • Machine Learning Using Neural Network
    • Adaptive Networks
    • Feed forward Networks
    • Supervised Learning Neural Networks
  • Unit-3.0: Radial Basis Function Networks
    • Reinforcement Learning
    • Unsupervised Learning Neural Networks
    • Adaptive Resonance architectures
    • Advances in Neural networks
  • Unit-4.0: Fuzzy Systems
    • Fuzzy Sets
    • Operations on Fuzzy Sets
    • Fuzzy Relations
    • Membership Functions: Fuzzy Rules and Fuzzy Reasoning
    • Fuzzy Inference Systems
    • Fuzzy Expert Systems
    • Fuzzy Decision Making
    • Fuzzy based Back Propagation network
  • Unit-5.0: Genetic Algorithm
    • Introduction to Genetic Algorithms (GA)
    • Applications of GA in Machine Learning: Machine Learning Approach to Knowledge Acquisition
    • GA based Back P
  • Unit-6.0: Matlab/Python Lib
    • Introduction to Matlab/Python
    • Arrays and array operations
    • Functions and Files
    • Study of neural network toolbox and fuzzy logic toolbox
    • Simple implementation of Artificial Neural Network and Fuzzy Logic

Text/Reference Books:

  1. Principles Of Soft Computing, 2nd Ed (With CD) Book by S. N. Deepa and S. N. Sivanandam
  2. Soft Computing, D. K. Pratihar, Narosa, 2008.
  3. Neural Networks, Fuzzy Logic and Genetic Algorithms: Synthesis & Applications, S.Rajasekaran, G. A. Vijayalakshami, PHI.
  4. Genetic Algorithms: Search and Optimization, E. Goldberg.
  5. Neuro-Fuzzy Systems, Chin Teng Lin, C. S. George Lee, PHI
  6. Build Neural Network With MS Excel sample by Joe choong.

Program Elective Course-II: Distributed Database [152608]

  • Unit-1.0: Concept And Overview Distributed Database System
    • What is Distributed Database System (DDBS)
    • Features of DDBS
    • Promises of DDBS
    • Design issue in DDBS
    • Distributed DBMS architecture:- Client/server System
    • Peer-to-Peer
    • Multi-Database system
  • Unit-2.0: Distributed Database Design
    • Distributed database design concept
    • Objective of Data Distribution
    • Data Fragmentation
    • The allocation of fragment
    • Transparencies in Distributed Database Design
  • Unit-3.0: Distributed Transaction And Concurrency Control
    • Basic concept of Transaction management
    • Objective Distributed transaction management
    • Model for Transaction management Distributed Concurrency control:- Objective
    • Concurrency control anomalies
    • Distributed Serializability
    • Locking based algorithm
  • Unit-4.0: Distributed Deadlock and Recovery
    • Introduction to Deadlock
    • Distributed Deadlock prevention
    • Avoidance
    • Detection and recovery
    • Two-Phase and Three-Phase Commit Protocol
  • Unit-5.0: Distributed Query Processing And Optimization
    • Concepts
    • Objective
    • And phases of distributed query processing
    • Join strategies in fragment relation
    • Global query optimization
  • Unit-6.0: Heterogeneous Database
    • Architecture of Heterogeneous Database
    • Database Integration: Schema Translation and schema Integration
    • Query processing issues in Heterogeneous database

Text/Reference Books:

  1. Silberschatz A, KorthHF, Sudarshan S, Database System Concepts, McGrall Hill.
  2. Ceri S, Pelagatti G, Distributed Databases - Principles and Systems, McGraw Hill.

Program Elective Course-II: Mobile and Wireless Computing [152609]

  • Unit-1.0: Introduction to Wireless Networks
    • Applications
    • History
    • Simplified Reference Model
    • Wireless transmission
    • Frequencies
    • Signals
    • Antennas
    • Signal propagation
    • Multiplexing
    • Modulation
    • Spread spectrum
    • Cellular Systems
  • Unit-2.0: MAC
    • Motivation
    • SDMA
    • FDMA
    • TDMA
    • CDMA
  • Unit-3.0: Telecommunication Systems
    • GSM
    • DECT
    • TETRA. UMTS
    • MT-2000
  • Unit-4.0: Wireless LAN
    • Infrared Vs Radio transmission
    • Infrastructure
    • Adhoc Network
    • 802.11
    • HIPERLAN
    • Bluetooth
    • Mobile Network Layer
    • Mobile IP
    • Dynamic Host Configuration Protocol
  • Unit-5.0: Adhoc Networks
    • Adhoc Networks
    • Mobile Transport Layer
    • Traditional TCP
    • Indirect TCP
    • Snooping TCP
    • Mobile TCP
    • Fast retransmit / Fast recovery
    • Transmission / Time-out freezing
    • Selective retransmission
    • Transaction Oriented TCP
  • Unit-6.0: Support for Mobility
    • Support for Mobility
    • File Systems
    • WWW
    • Wireless Application Protocol

Text/Reference Books:

  1. Jochen Schiller, "Mobile Communications", Pearson Education, Asia Publications, 2000.
  2. William Stallings, "Wireless Communication and Networks", PHI/Pearson Education, 2002.
  3. Kaveh Pahlavan, Prasanth Krishnamoorthy, "Principles of Wireless Networks", PHI/Pearson Education, 2003.
  4. Hazyszt of Wesolowshi, "Mobile Communication Systems", John Wiley and Sons Ltd, 2002.

Program Elective Course-II: Cloud Computing [152610]

  • Unit-1.0: Introduction
    • Distributed Computing and Enabling Technologies
    • Cloud Fundamentals: Cloud Definition
    • Evolution
    • Architecture
    • Applications
    • Deployment models
    • And service models
  • Unit-2.0: Virtualization
    • Issues with virtualization
    • Virtualization technologies and architectures
    • Internals of virtual machine monitors/hypervisors
    • Virtualization of data centers
    • And Issues with Multi-tenancy
  • Unit-3.0: Implementation
    • Study of Cloud computing Systems like Amazon EC2 and S3
    • Google App Engine
    • And Microsoft Azure
    • Build Private/Hybrid Cloud using open source tools
    • SLA management
  • Unit-4.0: Resource Management
    • Cloud resource provisioning plan (advance reservation, on demand plan, spot instances)
    • Various scheduling and load balancing techniques to improve QoS parameters
    • Resource Optimization algorithms
    • Task migration and VM migration technique
  • Unit-5.0: Security
    • Vulnerability Issues and Security Threats
    • Application-level Security
    • Data level Security
    • And Virtual Machine level Security
    • Infrastructure Security
    • And Multi-tenancy Issues
  • Unit-6.0: Advances
    • Green Cloud
    • Mobile Cloud Computing
    • Fog Computing
    • Internet of Things

Text/Reference Books:

  1. Cloud Computing Principles and Paradigms, Rajkumar Buyya, James Broberg, Andrzej Goscinski, Wiley Publishers 2011
  2. Cloud Computing Bible, Barrie Sosinsky, Wiley Publishers 2010
  3. Mastering Cloud computing, Rajkumar Buyya, Christian Vacchiola, S Thamarai Selvi, McGraw Hill 2013
  4. Cloud Security and Privacy: An Enterprise Perspective on Risks and Compliance, Tim Mather, Subra Kumaraswamy, Shahed Latif, O'Reilly 2010
  5. Cloud Computing by Shailendra Singh 2018

Program Elective Course-II: Data Mining [152611]

  • Unit-1.0: Data Warehousing and Business Analysis
    • Data warehousing Components
    • Building a Data warehouse
    • Data Warehouse Architecture
    • DBMS Schemas for Decision Support Data Extraction
    • Cleanup
    • And Transformation Tools
    • Metadata reporting Query tools and Applications Online Analytical Processing (OLAP)
    • OLAP and Multidimensional Data Analysis
  • Unit-2.0: Data Mining
    • Data Mining Functionalities
    • Data Preprocessing
    • Data Cleaning
    • Data Integration and Transformation
    • Data Reduction
    • Data Discretization and Concept Hierarchy Generation
    • Architecture of a Typical Data Mining Systems
    • Classification of Data Mining Systems
  • Unit-3.0: Association Rule Mining
    • Efficient and Scalable Frequent Item set Mining Methods
    • Mining Various Kinds of Association Rules
    • Association Mining to Correlation Analysis
    • Constraint Based Association Mining
  • Unit-4.0: Classification and Prediction
    • Issues Regarding Classification and Prediction
    • Classification by Decision Tree Introduction
    • Bayesian Classification
    • Rule Based Classification
    • Classification by Back propagation
    • Support Vector Machines
    • Associative Classification
    • Lazy Learners
    • Other Classification Methods Prediction Accuracy and Error Measures
    • Evaluating the Accuracy of a Classifier or Predictor
    • Ensemble Methods
    • Model Section
  • Unit-5.0: Cluster Analysis
    • Types of Data in Cluster Analysis
    • A Categorization of Major Clustering Methods Partitioning Methods
    • Hierarchical methods
    • Density-Based Methods
    • Grid-Based Methods
    • Model-Based Clustering Methods
    • Clustering High-Dimensional Data
    • Constraint-Based Cluster Analysis Outlier Analysis
  • Unit-6.0: Mining Object, Spatial, Multimedia, Text and Web Data
    • Multidimensional Analysis and Descriptive Mining of Complex Data Objects
    • Spatial Data Mining
    • Multimedia Data Mining
    • Text Mining
    • Mining the World Wide Web

Text/Reference Books:

  1. Jiawei Han, Micheline Kamber and Jian Pei, "Data Mining Concepts and Techniques", Third Edition, Elsevier, 2011.
  2. Alex Berson and Stephen J. Smith "Data Warehousing, Data Mining &OLAP", Tata McGraw Hill Edition, Tenth Reprint 2007.
  3. K.P. Soman, ShyamDiwakar and V. Ajay "Insight into Data mining Theory and Practice", Easter Economy Edition, Prentice Hall of India, 2006.
  4. G. K. Gupta "Introduction to Data Mining with Case Studies", Easter Economy Edition, Prentice Hall of India, 2006.
  5. Pang-Ning Tan, Michael Steinbach and Vipin Kumar "Introduction to Data Mining", Pearson Education, 2007.

Program Elective Course-III: Quantum Computing [152612]

  • Unit-1.0: Introduction to Quantum Computing
    • Motivation for studying Quantum Computing
    • Major players in the industry (IBM, Microsoft, Rigetti, D-Wave etc.)
    • Origin of Quantum Computing
    • Overview of major concepts in Quantum Computing
    • Qubits and multi-qubits states
    • Bra-ket notation
    • Bloch Sphere representation
    • Quantum Superposition
    • Quantum Entanglement
  • Unit-2.0: Math Foundation for Quantum Computing
    • Matrix Algebra: basis vectors and orthogonality
    • Inner product and Hilbert spaces
    • Matrices and tensors
    • Unitary operators and projectors
    • Dirac notation
    • Eigen values and Eigen vectors
  • Unit-3.0: Building Blocks for Quantum Program
    • Architecture of a Quantum Computing platform
    • Details of q-bit system of information representation: Block Sphere
    • Multi-qubits States
  • Unit-4.0: Quantum Superposition
    • Quantum superposition of qubits (valid and invalid superposition)
    • Quantum Entanglement
    • Useful states from quantum algorithmic perceptive e.g. Bell State
    • Operation on qubits: Measuring and transforming using gates
  • Unit-5.0: Quantum Logic gates and Circuit
    • Pauli
    • Hadamard
    • Phase shift
    • Controlled gates
    • Ising
    • Deutsch
    • Swap etc.
    • Programming model for a Quantum Computing Program: Steps performed on classical computer
    • Steps performed on Quantum Computer
    • Moving data between bits and qubits
  • Unit-6.0: Quantum Algorithms
    • Basic techniques exploited by quantum algorithms
    • Amplitude amplification
    • Quantum Fourier Transform
    • Phase Kick-back
    • Quantum Phase estimation
    • Quantum Walks
    • Major Algorithms: Shor's Algorithm
    • Grover's Algorithm
    • Deutsch's Algorithm
    • Deutsch Jozsa Algorithm
    • OSS Toolkits for implementing Quantum program: IBM quantum experience
    • Microsoft Q
    • Rigetti PyQuil (QPU/QVM)

Text/Reference Books:

  1. Michael A. Nielsen, "Quantum Computation and Quantum Information", Cambridge University Press.
  2. David McMahon, "Quantum Computing Explained", Wiley.
  3. IBM Experience: https://quantumexperience.ng.bluemix.net.
  4. Microsoft Quantum Development Kit https://www.microsoft.com/en-us/quantum/development-kit.
  5. Forest SDK PyQuil: https://pyquil.readthedocs.io/en/stable/.

Program Elective Course-III: Real Time Systems [152613]

  • Unit-1.0: Introduction
    • Hard vs. Soft real time systems
    • A reference model of real time system
    • Real-time scheduling: Clock driven approach
    • Weighted Round-robin approach
    • Priority driven approach
    • Dynamic vs. static system
    • Effective Release Times and Deadlines
    • EDF and LST algorithm
    • Optimality and Non-Optimality of the EDF and LST algorithms
    • Off line vs. online Scheduling
  • Unit-2.0: Clock-Driven Scheduling
    • Static
    • Time-Driven scheduler
    • General structure of Cyclic Schedules
    • Cyclic Executives
    • Improving the Average Response Time Of Aperiodic Jobs
    • Scheduling Sporadic Jobs
  • Unit-3.0: Priority Driven Scheduling Of Periodic Tasks
    • Fixe-priority vs. Dynamic priority algorithms
    • Maximum Schedulable Utilization
    • Optimality of the RM and DM algorithms
    • A Schedulability test for fixed-priority tasks with short response times
    • Sufficient Schedulability conditions for the RM and DM algorithms
  • Unit-4.0: Scheduling Aperiodic and Sporadic Jobs in Priority-Driven Systems
    • Assumptions and Approaches
    • Deferrable Servers
    • Sporadic Servers
    • Constant Utilization
    • Total Bandwidth and Weighted Fair-Queueing Servers
  • Unit-5.0: Resources and Resource Access control
    • Resource contention
    • Resource access control
    • Non-preemptive critical section
    • Basic Priority-Inheritance protocol
    • Basic Priority Ceiling Protocol
    • Stack based
    • Priority-ceiling protocol
    • Preemption ceiling protocol
  • Unit-6.0: Multiprocessor scheduling, Resource Access Control, and Synchronization
    • Model of multiprocessor & distributed systems
    • Task assignment
    • Multiprocessor Priority-ceiling protocol
    • Elements of Scheduling Algorithms For End-to-End Periodic Tasks- IPS protocols
    • PM protocols
    • MPM protocol

Text/Reference Books:

  1. Real-Time system by Jane W. S. Liu, Pearson Education
  2. Real-Time Systems by C. M. Krishna and K. G. Shin, McGraw Hill.

Program Elective Course-III: Bitcoin and Crypto Currencies [152614]

  • Unit-1.0: Introduction to Cryptography
    • Cryptographic Hash Functions
    • SHA-256
    • Hash Pointers and Data Structures
    • Merkle tree
  • Unit-2.0: Digital Signatures
    • Elliptic curve group
    • Elliptic Curve Digital Signature Algorithm (ECDSA)
    • Public Keys as Identities
    • A Simple Crypto currency
  • Unit-3.0: Centralization vs. Decentralization
    • Distributed consensus
    • Consensus without identity using a block chain
  • Unit-4.0: Incentives and proof of work
    • Bitcoin transactions
    • Bitcoin Scripts
    • Applications of Bitcoin scripts
    • Bitcoin blocks
    • The Bitcoin network
  • Unit-5.0: Simple Local Storage
    • Hot and Cold Storage
    • Splitting and Sharing Keys
    • Online Wallets and Exchanges
    • Payment Services
    • Transaction Fees
    • Currency Exchange Markets
  • Unit-6.0: Bitcoin Mining
    • Mining pools
    • Mining incentives and strategies
    • Bitcoin and Anonymity: Anonymity Basics
    • Mixing
    • Zerocoin and Zerocash

Text/Reference Books:

  1. Arvind Narayanan, Joseph Bonneau, Edward Felten, Andrew Miller and Steven Goldfeder, Bitcoin and Cryptocurrency Technologies, 2016.

Program Elective Course-III: Block Chain Technology [152615]

  • Unit-1.0: Introduction
    • Overview of Block chain
    • Public Ledgers
    • Bitcoin
    • Smart Contracts
    • Block in a Block chain
    • Transactions
    • Distributed Consensus
    • Public vs Private Block chain
    • Understanding Crypto currency to Block chain
    • Permissioned Model of Block chain
    • Overview of Security aspects of Block chain Basic Crypto Primitives: Cryptographic Hash Function
    • Properties of a hash function
    • Hash pointer and Merkle tree
    • Digital Signature
    • Public Key Cryptography
    • A basic crypto currency
  • Unit-2.0: Understanding Block chain with Crypto currency
    • Bitcoin and Block chain: Creation of coins
    • Payments and double spending
    • Bitcoin Scripts
    • Bitcoin P2P Network
    • Transaction in Bitcoin Network
    • Block Mining
    • Block propagation and block relay
  • Unit-3.0: Working with Consensus in Bitcoin
    • Distributed consensus in open environments
    • Consensus in a Bitcoin network
    • Proof of Work (PoW) - basic introduction
    • Hashcash PoW
    • Bitcoin PoW
    • Attacks on PoW and the monopoly problem
    • Proof of Stake
    • Proof of Burn and Proof of Elapsed Time
    • The life of a Bitcoin Miner
    • Mining Difficulty
    • Mining Pool
  • Unit-4.0: Understanding Block chain for Enterprises
    • Permissioned Block chain: Permissioned model and use cases
    • Design issues for Permissioned block chains
    • Execute contracts
    • State machine replication
    • Overview of Consensus models for permissioned block chain- Distributed consensus in closed environment
    • Paxos
    • RAFT Consensus
    • Byzantine general problem
    • Byzantine fault tolerant system
    • Lamport-Shostak-Pease BFT Algorithm
    • BFT over Asynchronous systems
  • Unit-5.0: Enterprise application of Block chain
    • Cross border payments
    • Know Your Customer (KYC)
    • Food Security
    • Mortgage over Block chain
    • Block chain enabled Trade
    • We Trade - Trade Finance Network
    • Supply Chain Financing
    • Identity on Block chain
  • Unit-6.0: Block chain application development
    • Hyperledger Fabric- Architecture
    • Identities and Policies
    • Membership and Access Control
    • Channels
    • Transaction Validation
    • Writing smart contract using Hyperledger Fabric
    • Writing smart contract using Ethereum
    • Overview of Ripple and Corda

Text/Reference Books:

  1. Melanie Swan, "Block Chain: Blueprint for a New Economy", O'Reilly, 2015.
  2. Josh Thompsons, "Block Chain: The Block Chain for Beginners- Guide to Block chain Technology and Leveraging Block Chain Programming".
  3. Daniel Drescher, "Block Chain Basics", Apress; 1st edition, 2017.
  4. Anshul Kaushik, "Block Chain and Crypto Currencies", Khanna Publishing House, Delhi.
  5. Imran Bashir, "Mastering Block Chain: Distributed Ledger Technology, Decentralization and Smart Contracts Explained", Packt Publishing.
  6. Ritesh Modi, "Solidity Programming Essentials: A Beginner's Guide to Build Smart Contracts for Ethereum and Block Chain", Packt Publishing.
  7. Salman Baset, Luc Desrosiers, Nitin Gaur, Petr Novotny, Anthony O'Dowd, Venkatraman Ramakrishna, "Hands-On Block Chain with Hyperledger: Building Decentralized Applications with Hyperledger Fabric and Composer", Import, 2018

Program Elective Course-III: Pattern Recognition [152616]

  • Unit-1.0: Introduction to Pattern Recognition
    • Definition
    • Applications of Pattern Recognition
    • Supervised vs. Unsupervised Learning
    • Statistical vs. Structural Pattern Recognition
    • Pattern Recognition System Design
    • Overview of Feature Extraction and Selection
  • Unit-2.0: Statistical Pattern Recognition
    • Bayes Decision Theory
    • Maximum Likelihood Estimation
    • Bayesian Classifier
    • Naïve Bayes Classifier
    • Parametric and Non-Parametric Approaches
    • K-Nearest Neighbors (KNN)
    • Probabilistic Graphical Models
  • Unit-3.0: Feature Extraction and Dimensionality Reduction
    • Feature Selection Techniques
    • Principal Component Analysis (PCA)
    • Linear Discriminant Analysis (LDA)
    • Independent Component Analysis (ICA)
    • Singular Value Decomposition (SVD)
    • Feature Engineering for Pattern Recognition
  • Unit-4.0: Machine Learning for Pattern Recognition
    • Support Vector Machines (SVM)
    • Decision Trees
    • Random Forest
    • Neural Networks (MLP, CNNs)
    • Deep Learning Approaches
    • Autoencoders
    • Performance Evaluation Metrics (Precision, Recall, F1-score, ROC Curve)
  • Unit-5.0: Clustering and Unsupervised Learning
    • K-Means Clustering
    • Hierarchical Clustering
    • DBSCAN
    • Gaussian Mixture Models (GMM)
    • Self-Organizing Maps (SOM)
    • Hidden Markov Models (HMM)
    • Applications of Clustering in Pattern Recognition
  • Unit-6.0: Applications and Emerging Trends
    • Pattern Recognition in Image Processing
    • Speech Recognition
    • Biometrics
    • Natural Language Processing (NLP)
    • Object Detection and Recognition
    • AI-driven Pattern Recognition
    • Ethical Considerations in Pattern Recognition

Text/Reference Books:

  1. Richard O. Duda, Peter E. Hart, David G. Stork - Pattern Classification, Wiley.
  2. Sergios Theodoridis, Konstantinos Koutroumbas - Pattern Recognition, Academic Press.
  3. C. M. Bishop - Pattern Recognition and Machine Learning, Springer.
  4. S. Haykin - Neural Networks and Learning Machines, Pearson.
  5. Christopher Bishop - Neural Networks for Pattern Recognition, Oxford University Press.
  6. S. V. N. Vishwanathan - Introduction to Statistical Learning Theory, Springer.
  7. Anil K. Jain, Robert P. Duin, Jianchang Mao Statistical Pattern Recognition: A Review, Elsevier.
  8. Trevor Hastie, Robert Tibshirani, Jerome Friedman The Elements of Statistical Learning, Springer.

Machine Learning Lab [152601P]

Perform all Experiments. List of Experiments:

  • 1. a) Implementation of Python Basic Libraries such as Statistics, Math, Numpy and Scipy.
    b) Implementation of Python Libraries for ML application such as Pandas and Matplotlib.
  • 2. a) Creation and Loading different datasets in Python.
    b) Write a python program to compute Mean, Median, Mode, Variance, Standard Deviation using Datasets
  • 3. a) Write a python program to compute reshaping the data, Filtering the data, merging the data and handling the missing values in datasets
  • 4. a) Write a Python program to implement Simple Linear Regression and plot the graph.
    b) Implementation of Multiple Linear Regression for House Price Prediction using sklearn
  • 5. Implementation of Logistic Regression for iris using sklearn
  • 6. Implementation of random forest algorithm
  • 7. Implementation of navie bayes classifier algorithm and plot the graph.
  • 8. Implementation of SVM classification and plot the graph.
  • 9. a) Implementation of PCA.
    b) Implementation of LDA.
  • 10. a) Implementation of k-means clustering.
    b) Implementation of hierarchical clustering

Web application Security Lab [152603P]

Perform all Experiments. List of Experiments:

  • 1. Install wireshark and explore the various protocols
    a. Analyze the difference between HTTP vs HTTPS
    b. Analyze the various security mechanisms embedded with different protocols.
  • 2. Identify the vulnerabilities using OWASP ZAP tool
  • 3. Create simple REST API using python for following operation.
    GET
    a. PUSH
    b. POST
    c. DELETE
  • 4. Install Burp Suite to do following vulnerabilities: SQL injection
    a. cross-site scripting (XSS)
  • 5. Attack the website using Social Engineering method

NPTEL Course-II Lab [152606P]

Details for NPTEL Course-II Lab will be provided by the department.

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