Information Technology — 6th Semester Syllabus

Unit-1.0:

Introduction: Phases of compilation and overview • Lexical Analysis (scanner): Regular languages • Finite automata • Regular expressions • From regular expressions to finite automata • Scanner generator (lex, flex)

Unit-2.0:

Syntax Analysis (Parser): Context-free languages and grammars • Push-down automata • LL(1) grammars and top-down parsing • Operator grammars • LR(O) • SLR(1) • LR(1) • LALR(1) grammars and bottom-up parsing • Ambiguity and LR parsing • LALR(1) parser generator (yacc, bison)

Unit-3.0:

Semantic Analysis: Attribute grammars • Syntax directed definition • Evaluation and flow of attribute in a syntax tree • Symbol Table: Its structure • Symbol attributes and management • Run-time environment: Procedure activation • Parameter passing • Value return • Memory allocation • And scope

Unit-4.0:

Intermediate Code Generation: Translation of different language features • Different types of intermediate forms • Code Improvement (optimization) Analysis: control-flow • Data-flow dependence etc. • Code improvement local optimization • Global optimization • Loop optimization and peep-hole optimization

Unit-5.0:

Architecture dependent code improvement: instruction scheduling (for pipeline) and loop optimization (for cache memory) • Register allocation and target code generation

Unit-6.0:

Advanced topics: Type systems • Data abstraction • Compilation of Object Oriented features and non-imperative programming languages

Unit-1.0: Cyber Security Fundamentals

Introduction • Cybercrime and Information Security • Classification of Cybercrimes • Cybercrime the legal Perspective • Cyberoffences • Cyber-attacks • Social engineering • Cyberstalking • Botnets • Attack Vector • Cybercrime and cloud computing • Cybercrimes on mobile and wireless devices • Attacks on mobile/cell phones

Unit-2.0: Authentication and Security Measures

Authentication service security • Organizational security policies and measures in mobile computing

Unit-3.0: Ethics in Cyber Security

Privacy • Intellectual Property in cyberspace • Professional Ethics • Freedom of Speech • Fair User and Ethical Hacking • Trademarks • Internet Fraud • Electronic Evidence • Forensic Technologies • Digital Evidence collection

Unit-4.0: Tools and Methods Used in Cybercrime

Introduction • Proxy Servers and Anonymizers • Phishing • Password Cracking • Keyloggers and Spywares • Virus and Worms • Phishing and Identity Theft • Trojan Horses and Backdoors • Steganography • DoS and DDoS Attacks • SQL Injection • Buffer overflows

Unit-5.0: Cybercrimes and Cyber security

Cybercrime and Legal Landscape around the world • Cyber laws • The Indian IT Act • Challenges • Digital Signatures and Indian IT Act • Amendments to the Indian IT Act • Cybercrime and punishment • Cost of Cybercrimes and IPR Issues • Web threats for Organizations • Social Computing and associated Challenges for Organizations

Unit-6.0: Cybercrime Examples and Mini-Cases

Career Paths in Cyber security • Honeypots • Case study (Official Website Hacking • E-mail spoofing • Banking related Frauds • Credit Card related Frauds)

Unit-1.0:

Introduction to Neural Network: Brief introduction to neural networks • Error Cost Function • Mean-Square Error • Cross-Entropy • Linear vs Nonlinear functions: Activation Function Linear • Sigmoid • Softmax • Relu

Unit-2.0:

Optimization: Gradient Descent Algorithm • Momentum Based Gradient Descent Algorithm and Nesterov Accelerated Gradient Descent Algorithm

Unit-3.0:

Algorithm for Pattern Association/Reconstruction: Associative memory networks • Hetero Associative Memory neural networks • Auto Associative Memory Networks • Bi-directional Associative memory networks • Feedback Networks: Discrete Hopfield Net • Continuous Hopfield Net • Radial Basis Function Networks (RBFN): Training algorithm for an RBFN with fixed Centres

Unit-4.0:

Cluster Network: Self-Organizing Feature Map • Plasticity/Stability Problem • Adaptive Resonance Theory (ARTI and ARTII) - Architecture • ARTMAP • Dense Embeddings: word2vec - Skip-gram model • Continuous Bag Of Words (CBOW) Model

Unit-5.0:

Convolutional Neural Network: Architecture • Convolution Operation • Filters • Pooling Operation - Max pooling • Average pooling • Global pooling • Dilated CNN

Unit-6.0:

Deep Recurrent Neural Network: Long Short Term Memory (LSTM) - Architecture • Gated Recurrent Unit-1.0:(GRU) • Attention Mechanism • Recursive Neural Network • Deep Unsupervised Learning: Autoencoders • Variational Autoencoders • Adversarial Generative Networks

Unit-1.0:

Computer Security concepts • OSI security Architecture • Security attacks • Security Services • Security Mechanisms • Model of network security • Standards • Physical Layer Security • Network device security

Unit-2.0:

Symmetric encryption Principles • Block cipher algorithms • Random and pseudorandom numbers • Stream ciphers and RC4 • Block cipher modes • Secure hash functions • Message authentication codes • Public-key-cryptography principles • Digital signature • Access control

Unit-3.0:

Key distribution and user authentication • Kerberos • X.509 Certificates • Federated identity management • Web security considerations • Secure Socket layer • Transport layer security • HTTPS 160 • Secure Shell(SSH) • IEEE 802.11i Wireless LAN Security • Wireless application protocol overview • Wireless transport layer security • WAP end-to-end security

Unit-4.0:

Electronic mail security • Pretty good privacy • S/MIME • Domain keys Identified Mail • IP Security overview • IP security Policy • Encapsulating security payload • Combining security association • Internet key exchange • DNSSec • eSMTPS • TCP session hijacking • ARP attacks • Route table modification • UDP hijacking • And man-in-the-middle attacks

Unit-5.0:

System Security- Types of malicious software • Viruses • Worms • DoS • DDoS • BOF • Countermeasures • IDS concepts • IDS types and detection models • IDS features • IDS deployment considerations • Firewalls characteristics • Types of Firewalls • Firewall location and Configuration

Unit-6.0:

Voice over IP (VoIP) and PBX security • VoIP components • VoIP vulnerabilities and countermeasures • Securing a PBX • Proxy or application level gateways as security devices • VPN • Privacy protection and anonymity services • Electronic payment system

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

Unit-1.0:

Overview of adversarial machine learning • Statistical machine learning • A framework for secure learning • Security analysis • Framework • Exploratory attacks • Causative attacks • Repeated learning games • Privacy-Preserving learning

Unit-2.0:

Attacking a hypersphere learner • Causative attacks on hypersphere detectors • Hypersphere attack description • Optimal unconstrained attacks • Imposing time constraints on the attack • Attacks against retraining with data replacements • Constrained attackers

Unit-3.0:

Availability attack Case Study: SpamBayes • Spam Filter • Threat model • Causative attacks • RONI Defense • Experiments with SpamBayes

Unit-4.0:

Integrity Attack Case Study: PCA Detector • Traffic anomalies • Corrupting the PCA subspace • Corruption-Resilient Detectors • Empirical evaluation

Unit-5.0:

Privacy-Preserving Mechanism for SVM learning • Privacy Breach case studies • Problem setting: privacy-preserving learning • Support Vector Machines: A brief primer • Differential privacy

Unit-6.0:

Near optimal evasion of classifiers • Convex classes • Adversarial machine learning challenges • Open problems • Defensive technologies

Unit-1.0:

Introduction: Motivation for distributed systems • Characteristics of distributed systems and middleware categories • Network service requirements for distributed systems • Architectural models of distributed systems • Interprocess communication: Multithreading models and multithreaded client/server architectures • Hardware virtualization • Code mobility • Virtual machine migration • Interprocess communication paradigms in distributed systems

Unit-2.0:

Naming: Naming scheme and namespace • URI • URN • URL • Name resolution and DNS naming service • Naming and location services of mobile entities • Distributed garbage collection • Synchronization: Clock synchronization • NTP and GPS • Lamport's clock and vector clock • Total-ordered and causal-ordered multicasting • Election and mutual exclusion in distributed systems • Coordination: Coordination models • Direct and indirect coordination • Gossip based and group coordination • Publish-subscribe coordination

Unit-3.0:

Consistency: Consistency models • Data-centric and client-centric consistency • Linearizability • Sequential • Causal and FIFO consistency • Eventual consistency • Monotonic read/write • Read-your-writes • Writes-follow-reads consistency • Replication: Replication system architecture and functioning • Passive and active replication • Replication in gossip architecture • Consistency models and protocols in replication • Continuous consistency and conit • Replica management • Placement and distribution

Unit-4.0:

Fault Tolerance: Dependability • Failure model • Failure handling and resiliency • Reliable group communication • Distributed commit and consensus • Failure Recovery: Forward-error and backward-error recovery • Rollback and checkpointing • Message logging

Unit-5.0:

Distributed object-based and component-based systems: Distributed objects • Object servers and adapters • Distributed components and containers • Distributed event-based systems: Distributed event-based system architectures • Communication • Matching and filtering • Content-based

Unit-6.0:

Distributed web-based systems: Web service descriptions • SOAP and REST protocol • UDDI service • Web servers and web server clusters • Distributed file systems: Distributed file system design requirements • File service architecture • Pervasive systems: Sensor • Actuator and IoT • Ubiquity • Sensor network • Context awareness

Unit-1.0: Introduction

Overview of wireless and mobile infrastructure • Preliminary concepts on cellular architecture • Design objectives and performance issues • Radio resource management and interface • Propagation and path loss models • Channel interference and frequency reuse • Cell splitting • Channel assignment strategies • Overview of generations: - 1G to 5G

Unit-2.0: Location Management

Introduction to location management (HLR and VLR) • Mobility models characterizing individual node movement (Random walk • Fluid flow • Markovian • Activity based) • Mobility models characterizing the movement of groups of nodes (Reference point based group mobility model • Community based group mobility model) • Static (Always vs. Never update • Reporting Cells • Location Areas) and Dynamic location management schemes (Time • Movement • Distance • Profile Based) • Terminal Paging (Simultaneous paging • Sequential paging) • Location management and Mobile IP

Unit-3.0: Handoff Management

Overview of handoff process • Factors affecting handoffs and performance evaluation metrics • Handoff strategies • Different types of handoffs (soft • Hard • Horizontal • Vertical)

Unit-4.0: Basics of Wireless Transmission

Introduction to narrow and wideband systems • Spread spectrum • Frequency hopping • Introduction to MIMO • MIMO Channel Capacity and diversity gain • Introduction to OFDM • MIMO-OFDM system • Multiple access control (FDMA • TDMA • CDMA • SDMA) • Wireless local area network • Wireless personal area network (Bluetooth and Zigbee)

Unit-5.0: Cognitive Radio Networks

Fixed and dynamic spectrum access • Direct and indirect spectrum sensing • Spectrum sharing • Interoperability and co-existence issues • Applications of cognitive radio networks

Unit-6.0: Basics Of 5g Networks

Introduction to D2D communications • High level requirements for 5G architecture • Introduction to the radio resource management • Power control and mode selection problems • Milli-meterwave communication in 5G

Unit-1.0:

Network Attacks • Understanding Intrusion Detection and Intrusion Prevention System • Detection Approaches (Misuse Detection • Anomaly Detection • Etc.) • Uses of IDPS Technologies • Key Functions of IDPS Technologies • Stateful Protocol Analysis

Unit-2.0:

Data Collection (Host-Based • Network-Based • Application-Based • Application-Integrated and Hybrid) • Theoretical Foundations of Detection Taxonomy of anomaly detection system • Fuzzy logic • Bayes theorem • Artificial Neural networks • Support vector machine • Evolutionary computation • Association rules • Clustering • Architecture and Implementation

Unit-3.0:

IDS Challenges • Alert Management & Correlation (Data Fusion • Alert Correlation • Cooperative Intrusion Detection) • Evaluation Criteria- Accuracy • Performance • Completeness • Timely Response • Adaptation and Cost-Sensitivity • Intrusion Tolerance and Attack Resistance • Test • Intrusion Response

Unit-4.0:

Security and IDS Management (Data Correlation • Incident Response • Policy and Procedures • Law • Standards and organizations • Security Business issues • Future of Intrusion Detection and Prevention)

Unit-5.0:

Implementation and Deployment: Internet Security System's Real Source • Snort • NFR Security • IDS Tools • Detailed case study of IDS in different networks like Ethernet Networks • 802.11 Networks • Mobile Networks • Ad-hoc Networks • And Wireless Sensor Networks

Unit-6.0:

Introduction to Snort • Different modes of Snort • Snort IDS Components • Snort Rules • Snort Filters • Snort output • Alert modes

Unit-1.0:

Sound: Biology of Speech Processing • Place and Manner of Articulation • Word Boundary Detection • Argmax based computations • HMM and Speech Recognition

Unit-2.0:

Words and Word Forms: Morphology fundamentals • Morphological Diversity of Indian Languages • Morphology Paradigms • Finite State Machine Based Morphology • Automatic Morphology Learning • Shallow Parsing • Named Entities • Maximum Entropy Models • Random Fields

Unit-3.0:

Structures: Theories of Parsing • Parsing Algorithms • Robust and Scalable Parsing on Noisy Text as in Web documents

Unit-4.0:

Hybrid of Rule Based and Probabilistic Parsing • Scope Ambiguity and Attachment Ambiguity resolution

Unit-5.0:

Meaning: Lexical Knowledge Networks • Wordnet Theory • Indian Language Wordnets and Multilingual Dictionaries • Semantic Roles • Word Sense Disambiguation • WSD and Multilinguality • Metaphors • Coreferences

Unit-6.0:

Web 2.0 Applications: Sentiment Analysis • Text Entailment • Robust and Scalable Machine Translation • Question Answering in Multilingual Setting • Cross Lingual Information Retrieval (CLIR)

Unit-1.0: Introduction to Reinforcement Learning Problem

Reinforcement Learning • Elements of Reinforcement Learning • Limitations and Scope • An Extended Example: Tic-Tac-Toe • History of Reinforcement Learning

Unit-2.0: Multi-arm Bandits

An n-Armed Bandit Problem • Action-Value Methods • Incremental Implementation • Tracking a Nonstationary Problem • Optimistic Initial Values • Upper-Confidence-Bound

Unit-3.0: Finite Markov Decision Processes

The Agent-Environment Interface • Goals and Rewards • Returns • Unified Notation for Episodic and Continuing Tasks • The Markov Property • Markov Decision Processes • Value Functions • Optimal Value Functions • Optimality and Approximation

Unit-4.0: Dynamic Programming

Policy Evaluation • Policy Improvement • Policy Iteration • Value Iteration • Asynchronous Dynamic Programming • Generalized Policy Iteration • Efficiency of Dynamic Programming

Unit-5.0: BMonte Carlo Methods

Monte Carlo Prediction • Monte Carlo Estimation of Action Values • Monte Carlo Control • Monte Carlo Control without Exploring Starts • Off-policy Prediction via Importance Sampling • Incremental Implementation • Off-Policy Monte Carlo Control • Importance Sampling on Truncated Returns

Unit-6.0: Temporal-Difference Learning and Policy Approximation

TD Prediction • Advantages of TD Prediction Methods • Optimality of TD(0) • Sarsa: On-Policy TD Control • Q-Learning: Off-Policy TD Control • Games • Actor-Critic Methods • Eligibility Traces for Actor-Critic Methods • R-Learning and the Average-Reward Setting • Vanilla policy gradient method