IT- 801 – Information Security
Unit I:
Basic of Cryptography, secret key cryptography, Types of attack, Substitution ciphers,
Transposition ciphers, block ciphers and steam ciphers, Confusion and Diffusion, Data encryption
standard, round function, modes of operation, cryptanalysis, brute force attack, Security Goals
(Confidentiality, Integrity, Availability).
Unit II:
Public key Cryptography, Modulo arithmetic, Greatest common divisor, Euclidean
algorithm, RSA algorithm, hash function, attack on collision resistance, Diffie hellman key
exchange, Digital signature standard, elliptic curve cryptography.
Unit III:
Authentication: One way Authentication, password based, certificate based, Mutual
Authentication ,shared secret based, Asymmetric based, Authentication and key agreement,
centralized Authentication, eavesdropping, Kerberos, IP security overview:- security association &
Encapsulating security payload ,tunnel and transfer modes, internet key exchange protocol, Secure
Socket Layer(SSL), Transport Layer Security (TLS).
Unit IV:
Software vulnerabilities: Phishing Attacks, buffer overflow vulnerability, Format String
attack, Cross Site Scripting, SQL injection Attacks, Email security:- Security services of E-mail
,Establishing keys, Privacy ,Authentication of the source, Message integrity ,Non-Repudiation,
Viruses, Worms, Malware.
Unit V:
Web Issue: Introduction, Uniform Resource Locator/uniform resource identify, HTTP,
Cookies, Web security problem, Penetration Testing, Firewalls:- functionality, Polices and Access
Control, Packet filters, Application level gateway, Encrypted tunnel, Security architecture,
Introduction to intrusion detection system.
List of Experiment:-
Study of Network Security fundamentals - Ethical Hacking, Social Engineering practices.
System threat attacks - Denial of Services.
Sniffing and Spoofing.
Web Based Password Capturing.
Virus and Trojans.
Anti-Intrusion Technique – Honey pot.
Symmetric Encryption Scheme – RC4.
Block Cipher – S-DES, 3-DES.
Asymmetric Encryption Scheme – RSA.
IP based Authentication.
IT- 802 – Soft Computing
Unit I:
Introduction to Neural Network: Concept, biological neural network, evolution of artificial
neural network, McCulloch-Pitts neuron models, Learning (Supervise & Unsupervise) and
activation function, Models of ANN-Feed forward network and feed back network, Learning Rules-
Hebbian, Delta, Perceptron Learning and Windrow-Hoff, winner take all.
Unit II:
Supervised Learning: Perceptron learning- Single layer/multilayer, linear Separability,
Adaline, Madaline, Back propagation network, RBFN. Application of Neural network in forecasting,
data compression and image compression.
Unit III:
Unsupervised learning: Kohonen SOM (Theory, Architecture, Flow Chart, Training
Algorithm) Counter Propagation (Theory , Full Counter Propagation NET and Forward only counter
propagation net), ART (Theory, ART1, ART2). Application of Neural networks in pattern and face
recognition, intrusion detection, robotic vision.
Unit IV:
Fuzzy Set: Basic Definition and Terminology, Set-theoretic Operations, Member Function,
Formulation and Parameterization, Fuzzy rules and fuzzy Reasoning, Extension Principal and
Fuzzy Relations, Fuzzy if-then Rules, Fuzzy Inference Systems. Hybrid system including neuro
fuzzy hybrid, neuro genetic hybrid and fuzzy genetic hybrid, fuzzy logic controlled GA. Application
of Fuzzy logic in solving engineering problems.
Unit V:
Genetic Algorithm: Introduction to GA, Simple Genetic Algorithm, terminology and
operators of GA (individual, gene, fitness, population, data structure, encoding, selection,
crossover, mutation, convergence criteria). Reasons for working of GA and Schema theorem, GA
optimization problems including JSPP (Job shop scheduling problem), TSP (Travelling salesman
problem), Network design routing, timetabling problem. GA implementation using MATLAB.
List of Experiment:-
Form a perceptron net for basic logic gates with binary input and output.
Using Adaline net, generate XOR function with bipolar inputs and targets.
Calculation of new weights for a Back propagation network, given the values of input
pattern, output pattern, target output, learning rate and activation function.
Construction of Radial Basis Function Network.
Use of Hebb rule to store vector in auto associative neural net.
Use of ART algorithm to cluster vectors.
Design fuzzy inference system for a given problem.
Maximize the function y =3x2 + 2 for some given values of x using Genetic algorithm.
Implement Travelling salesman problem using Genetic Algorithm.
Optimisation of problem like Job shop scheduling using Genetic algorithm.
IT830- Component Based Software Engineering
Unit I:
Introduction to Component Based Development: Definition of Software Component and
its Elements, The Component Industry Metaphor, Component Models and Component Services:
Concepts and Principles, An Example Specification for Implementing a Temperature Regulator
Software Component.
Unit II:
Case for Components: The Business Case for Software Components, COTS Myths and
Other Lessons Learned in Component-Based Software Development, Roles for Component-Based
Development, Common High Risk Mistakes in Component-Based Software Engineering, CBSE
Success Factors: Integrating Architecture, Process, and Organization
Unit III:
Software Component Infrastructure: Software Components and the UML, Component
Infrastructures: Placing Software Components in Context, Business Components, Components
and Connectors: Catalysis Techniques for Defining Component Infrastructures, an Open Process
for Component-Based Development, Designing Models of Modularity and Integration.
Unit IV:
Management of CBD: Measurement and Metrics for Software Components, The Practical
Reuse of Software Components, Selecting the Right COTS Software: Why Requirements are
important, Build vs. Buy, Software Component Project Management Processes, The Trouble with
Testing Software Components, Configuration Management and Component Libraries, The
Evolution, Maintenance and Management of Component-Based Systems
Unit V:
Component Technologies: Overview of the CORBA Component Model, Transactional
COM+ Designing Scalable Applications, The Enterprise JavaBeans Component Model, Choosing
Between COM+, EJB, and CCM, Software Agents as Next Generation Software Components,
IT831-Real Time Systems
Unit I:
Introduction to real time systems, structure, issues, task classes, performance measures for
real time systems-their properties, traditional measures, cost functions and hard deadlines.
Estimation of program run time-source code analysis, accounting for pipelining and caches.
Unit II:
Task Assignment and Scheduling-Rate monotonic scheduling algorithm, Preemptive
earliest deadline first algorithm, Using primary and alternative tasks. Task Assignment-Utilization
balancing algorithm, next fit for RM(Rate monitoring) scheduling, Bin packing assignment algorithm
for EDF, Myopic offline scheduling(MOS) algorithm, Focused addressing and bidding(FAB)
algorithm, Buddy strategy, Assignment with precedence conditions.
Unit III:
Programming Languages & Tools- Desired language characteristics,, data typing, control
structures, hierarchical decomposition, packages, run time error handling, Overloading and
genetics, Multitasking, Low level programming, Fex, Euclid, Run time support.
Unit IV:
Real time Communication-Communication media, network topologies. Protocols-
Contention based, Token based, Stop-and-Go, Polled bus, Hierarchical round robin, deadline
based.
Unit V:
Fault Tolerance Techniques- Fault, fault types, fault detection, fault and error containment,
hardware and software redundancy, time redundancy, information redundancy. Reversal checks,
Malicious or Byzantine failures, Integrated failure handling.
IT832 Image processing
Unit I:
Image representation, fundamental steps in image processing, image model. Sampling &
quantization. Neighbors of a pixel, connectivity and distance measures. Basic transformations and
perspective transformations. Two dimensional Fourier transform, Discrete Fourier transform and
their properties. Fast Fourier transform, Walsh Transform, Hadamard transform and Discrete
Cosine transform.
Unit II:
Image Enhancement: Intensity transformations, histogram processing, Image subtraction,
image averaging, Spatial filtering-smoothing and sharpening filters, frequency domain filtering
methods-low pass filtering, high pass filtering, median filtering.
Unit III:
Image compression: Redundancy and its types. Image compression model, variable
length coding, bit plane coding, constant area coding, run length coding, lossless and lossy
predictive coding, transform coding.
Unit IV:
Image restoration and Segmentation: Degradation model, effect of diagonalisation on
degradation, algebraic approach. Detection of discontinuities by point, line and edge detection.
Edge linking, graph theoretic techniques, thresholding techniques, region oriented segmentation.
Unit V:
Representation & Description: Chain codes, polygonal approximations, signatures,
boundary segments, skeleton, boundary descriptors, shape descriptors regional descriptors, image
morphology-dilation, erosion, opening, closing, thickening, thinning, skeleton, pruning,, hit or miss
transform.
IT 833 Artificial Intelligence
Unit I:
Meaning and definition of artificial intelligence, Various types of production systems,
Characteristics of production systems, Study and comparison of breadth first search and depth first
search. Techniques, other Search Techniques like hill Climbing, Best first Search. A* algorithm,
AO* algorithms etc, and various types of control strategies.
Unit II:
Knowledge Representation, Problems in representing knowledge, knowledge
representation using propositional and predicate logic, comparison of propositional and predicate
logic, Resolution, refutation, deduction, theorem proving, inferencing, monotonic and nonmonotonic
reasoning.
Unit III:
Probabilistic reasoning, Baye's theorem, semantic networks, scripts, schemas, frames,
conceptual dependency, fuzzy logic, forward and backward reasoning.
Unit IV:
Game playing techniques like minimax procedure, alpha-beta cut-offs etc, planning, Study
of the block world problem in robotics, Introduction to understanding and natural languages
processing.
Unit V:
Introduction to learning, Various techniques used in learning, introduction to neural
networks, applications of neural networks, common sense, reasoning, some example of expert
systems.
IT840-Data Mining & Warehousing
Unit I:
Data Warehousing: Need for data warehousing , Basic elements of data warehousing,
Data Mart, Data Warehouse Architecture, extract and load Process, Clean and Transform data,
Star ,Snowflake and Galaxy Schemas for Multidimensional databases, Fact and dimension data,
Partitioning Strategy-Horizontal and Vertical Partitioning.
Unit II:
Data Warehouse and OLAP technology, Multidimensional data models and different OLAP
Operations, OLAP Server: ROLAP, MOLAP, Data Warehouse implementation ,Efficient
Computation of Data Cubes, Processing of OLAP queries, Indexing data.
Unit III:
Data Mining: Data Preprocessing ,Data Integration and Transformation, Data Reduction,
Discretizaion and Concept Hierarchy Generation , Basics of data mining, Data mining techniques,
KDP (Knowledge Discovery Process), Application and Challenges of Data Mining, Introduction of
Web Structure Mining, Web Usage Mining, Spatial Mining, Text Mining, Security Issue, Privacy
Issue, Ethical Issue.
Unit IV:
Mining Association Rules in Large Databases: Association Rule Mining, Single-
Dimensional Boolean Association Rules, Multi-Level Association Rule, Apriori Algorithm, Fp-
Growth Algorithm, Time series mining association rules, latest trends in association rules mining.
Unit V:
Classification and Clustering Distance Measures, Types of Clustering, K-Means Algorithm,
Decision Tree Induction, Bayesian Classification, Association Rule Based, Other Classification
Methods,
Prediction, Classifier Accuracy, Categorization of methods, Partitioning methods, Outlier Analysis.
IT841-Cyber law & Forensic
Unit I:
Cyber world: an overview, internet and online resources, security of information, digital
signature, intellectual property (IP), historical background of IP, IPR governance, National patent
offices, the world intellectual property organization (WIPO).
Unit II:
Introduction about the cyber space, cyber law, regulation of cyber space, scope of cyber
laws: ecommerce; online contracts; IPRs (copyright, trademarks and software patenting), etaxation;
e-governance and cyber crimes, cyber law in India with special reference to Information
Technology Act, 2000.
Unit III:
Introduction to computer and cyber crimes. Cyber crimes and related concepts, distinction
between cyber crimes and conventional crimes, Cyber criminals and their objectives. Kinds of
cyber crimes cyber stalking; cyber pornography, forgery and fraud, crime related to IPRs, cyber
terrorism; computer vandalism etc. Cyber forensics, computer forensics and the law, forensic
evidence, computer forensic tools.
Unit IV:
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.
Unit V:
Copyright issues in cyberspace: linking, framing, protection of content on web site,
international treaties, trademark issues in cyberspace: domain name dispute, cyber squatting,
uniform dispute resolution policy, computer software and related IPR issues.
IT842- Adhoc Network
Unit I
Introduction :Introduction-Fundamentals of Wireless Communication Technology, The
Electromagnetic Spectrum, GSM, GPRS, PCS, WLAN and UMTS, Components of Packet Radios,
Routing in PRNETs, Route calculation, Pacing techniques, Ad Hoc Wireless Networks,
Heterogeneity in Mobile Devices, Wireless Sensor Networks, Traffic Profiles, Types of Ad Hoc
Mobile Communications, Types of Mobile Host Movements, Challenges Facing Ad Hoc Mobile
Networks.
Unit II
Ad Hoc wireless MAC protocols- Introduction, Synchronous and asynchronous MAC
protocols, Problem in Ad Hoc channel access, Receiver-initiated and sender-initiated MAC
protocols, Existing Ad Hoc MAC protocols, Ad Hoc Routing Protocols- Introduction, Issues in
Designing a Routing Protocol for Ad Hoc Wireless Networks, Classifications of Routing Protocols:
Table-Driven Routing Protocols – Destination Sequenced Distance Vector (DSDV), Wireless
Routing Protocol (WRP), Cluster Switch Gateway Routing (CSGR), Source-Initiated On-Demand
Approaches - Ad Hoc On-Demand Distance Vector Routing (AODV), Dynamic Source Routing
(DSR), Temporally Ordered Routing Algorithm (TORA), Signal Stability Routing (SSR) Location-
Aided Routing (LAR), Power-Aware Routing (PAR), Zone Routing Protocol (ZRP).
Unit III
Multicast routing In Ad Hoc Networks : Introduction, Issues in Designing a Multicast
Routing Protocol, Operation of Multicast Routing Protocols, An Architecture Reference Model for
Multicast Routing Protocols, Classifications of Multicast Routing Protocols, Tree-Based Multicast
Routing Protocols, Mesh- Based Multicast Routing Protocols, Summary of Tree-and Mesh-Based
Protocols - Energy-Efficient Multicasting, Multicasting with Quality of Service Guarantees,
Application Dependent Multicast Routing, Comparisons of Multicast Routing Protocols.
Unit IV
Transport Layer, Security Protocols : Introduction, Issues in Designing a Transport Layer
Protocol for Ad Hoc Wireless Networks, Design Goals of a Transport Layer Protocol for Ad Hoc
Wireless Networks, Classification of Transport Layer Solutions, TCP Over Ad Hoc Wireless
Networks, Other Transport Layer Protocols for Ad Hoc Wireless Networks, Security in Ad Hoc
Wireless Networks, Network Security Requirements, Issues and Challenges in Security
Provisioning, Network Security Attacks, Key Management, Secure Routing in Ad Hoc Wireless
Networks.
Unit V
QoS and Energy Management : Introduction, Issues and Challenges in Providing QoS in
Ad Hoc Wireless Networks, Classifications of QoS Solutions, MAC Layer Solutions, Network Layer
Solutions, QoS Frameworks for Ad Hoc Wireless Networks, Energy Management in Ad Hoc
Wireless Networks – Introduction, Need for Energy Management in Ad Hoc Wireless Networks,
Classification of Energy Management Schemes, Battery Management Schemes, Transmission
Power Management Schemes, System Power Management Schemes.
IT843 - Operation Research
Unit I:
Introduction to Linear Programming, Solution by Graphical and Simplex Method, Concept of
Degeneracy and Duality, Artificial Variable Techniques : Big-M Method, Two Phase Method ,
Solution of Transportation Problems by North-West Corner Method, Lowest Cost Entry Method,
Vogel’s Method, Non- Degenerate Basic Feasible Solution, Assignment Model
Unit II:
Integer Programming: Relationship to Linear Programming, Branch and Bound, Cutting
Plane Techniques: General Cutting Planes , Dynamic Programming: Introduction, Bellman’s
Principle of optimality, Applications of dynamic programming, Critical Path Method, PERT
Unit III:
Replacement, Introduction, Replacement of items that deteriorate with time when money
value is not counted and counted, Replacement of items that fail completely, group replacement.
Games Theory: Introduction, Minimax (maximin), Criterion and optimal strategy, Solution of games
with saddle points, Rectangular games without saddle points, 2 X 2 games, dominance principle–
m X 2 & 2 X n games.
Unit IV:
Inventory : Introduction , Single item – Deterministic models, Purchase inventory models
with one price break and multiple price breaks shortages are not allowed , Stochastic models
demand may be discrete variable or continuous variable, Instantaneous production. Instantaneous
demand and continuous demand and no set up cost.
Unit V:
Waiting Lines: Introduction, Single Channel, Poisson arrivals, exponential service times
with infinite population and finite population models, Multi channel, Poisson arrivals, exponential
service times with infinite population single channel Poisson arrivals: (M/M/1 : /FCFS), (M/M/1 :
N/FCFS), (M/Ek/1 : /FCFS), (M/M/S : /FCFS)
Unit I:
Basic of Cryptography, secret key cryptography, Types of attack, Substitution ciphers,
Transposition ciphers, block ciphers and steam ciphers, Confusion and Diffusion, Data encryption
standard, round function, modes of operation, cryptanalysis, brute force attack, Security Goals
(Confidentiality, Integrity, Availability).
Unit II:
Public key Cryptography, Modulo arithmetic, Greatest common divisor, Euclidean
algorithm, RSA algorithm, hash function, attack on collision resistance, Diffie hellman key
exchange, Digital signature standard, elliptic curve cryptography.
Unit III:
Authentication: One way Authentication, password based, certificate based, Mutual
Authentication ,shared secret based, Asymmetric based, Authentication and key agreement,
centralized Authentication, eavesdropping, Kerberos, IP security overview:- security association &
Encapsulating security payload ,tunnel and transfer modes, internet key exchange protocol, Secure
Socket Layer(SSL), Transport Layer Security (TLS).
Unit IV:
Software vulnerabilities: Phishing Attacks, buffer overflow vulnerability, Format String
attack, Cross Site Scripting, SQL injection Attacks, Email security:- Security services of E-mail
,Establishing keys, Privacy ,Authentication of the source, Message integrity ,Non-Repudiation,
Viruses, Worms, Malware.
Unit V:
Web Issue: Introduction, Uniform Resource Locator/uniform resource identify, HTTP,
Cookies, Web security problem, Penetration Testing, Firewalls:- functionality, Polices and Access
Control, Packet filters, Application level gateway, Encrypted tunnel, Security architecture,
Introduction to intrusion detection system.
List of Experiment:-
Study of Network Security fundamentals - Ethical Hacking, Social Engineering practices.
System threat attacks - Denial of Services.
Sniffing and Spoofing.
Web Based Password Capturing.
Virus and Trojans.
Anti-Intrusion Technique – Honey pot.
Symmetric Encryption Scheme – RC4.
Block Cipher – S-DES, 3-DES.
Asymmetric Encryption Scheme – RSA.
IP based Authentication.
IT- 802 – Soft Computing
Unit I:
Introduction to Neural Network: Concept, biological neural network, evolution of artificial
neural network, McCulloch-Pitts neuron models, Learning (Supervise & Unsupervise) and
activation function, Models of ANN-Feed forward network and feed back network, Learning Rules-
Hebbian, Delta, Perceptron Learning and Windrow-Hoff, winner take all.
Unit II:
Supervised Learning: Perceptron learning- Single layer/multilayer, linear Separability,
Adaline, Madaline, Back propagation network, RBFN. Application of Neural network in forecasting,
data compression and image compression.
Unit III:
Unsupervised learning: Kohonen SOM (Theory, Architecture, Flow Chart, Training
Algorithm) Counter Propagation (Theory , Full Counter Propagation NET and Forward only counter
propagation net), ART (Theory, ART1, ART2). Application of Neural networks in pattern and face
recognition, intrusion detection, robotic vision.
Unit IV:
Fuzzy Set: Basic Definition and Terminology, Set-theoretic Operations, Member Function,
Formulation and Parameterization, Fuzzy rules and fuzzy Reasoning, Extension Principal and
Fuzzy Relations, Fuzzy if-then Rules, Fuzzy Inference Systems. Hybrid system including neuro
fuzzy hybrid, neuro genetic hybrid and fuzzy genetic hybrid, fuzzy logic controlled GA. Application
of Fuzzy logic in solving engineering problems.
Unit V:
Genetic Algorithm: Introduction to GA, Simple Genetic Algorithm, terminology and
operators of GA (individual, gene, fitness, population, data structure, encoding, selection,
crossover, mutation, convergence criteria). Reasons for working of GA and Schema theorem, GA
optimization problems including JSPP (Job shop scheduling problem), TSP (Travelling salesman
problem), Network design routing, timetabling problem. GA implementation using MATLAB.
List of Experiment:-
Form a perceptron net for basic logic gates with binary input and output.
Using Adaline net, generate XOR function with bipolar inputs and targets.
Calculation of new weights for a Back propagation network, given the values of input
pattern, output pattern, target output, learning rate and activation function.
Construction of Radial Basis Function Network.
Use of Hebb rule to store vector in auto associative neural net.
Use of ART algorithm to cluster vectors.
Design fuzzy inference system for a given problem.
Maximize the function y =3x2 + 2 for some given values of x using Genetic algorithm.
Implement Travelling salesman problem using Genetic Algorithm.
Optimisation of problem like Job shop scheduling using Genetic algorithm.
IT830- Component Based Software Engineering
Unit I:
Introduction to Component Based Development: Definition of Software Component and
its Elements, The Component Industry Metaphor, Component Models and Component Services:
Concepts and Principles, An Example Specification for Implementing a Temperature Regulator
Software Component.
Unit II:
Case for Components: The Business Case for Software Components, COTS Myths and
Other Lessons Learned in Component-Based Software Development, Roles for Component-Based
Development, Common High Risk Mistakes in Component-Based Software Engineering, CBSE
Success Factors: Integrating Architecture, Process, and Organization
Unit III:
Software Component Infrastructure: Software Components and the UML, Component
Infrastructures: Placing Software Components in Context, Business Components, Components
and Connectors: Catalysis Techniques for Defining Component Infrastructures, an Open Process
for Component-Based Development, Designing Models of Modularity and Integration.
Unit IV:
Management of CBD: Measurement and Metrics for Software Components, The Practical
Reuse of Software Components, Selecting the Right COTS Software: Why Requirements are
important, Build vs. Buy, Software Component Project Management Processes, The Trouble with
Testing Software Components, Configuration Management and Component Libraries, The
Evolution, Maintenance and Management of Component-Based Systems
Unit V:
Component Technologies: Overview of the CORBA Component Model, Transactional
COM+ Designing Scalable Applications, The Enterprise JavaBeans Component Model, Choosing
Between COM+, EJB, and CCM, Software Agents as Next Generation Software Components,
IT831-Real Time Systems
Unit I:
Introduction to real time systems, structure, issues, task classes, performance measures for
real time systems-their properties, traditional measures, cost functions and hard deadlines.
Estimation of program run time-source code analysis, accounting for pipelining and caches.
Unit II:
Task Assignment and Scheduling-Rate monotonic scheduling algorithm, Preemptive
earliest deadline first algorithm, Using primary and alternative tasks. Task Assignment-Utilization
balancing algorithm, next fit for RM(Rate monitoring) scheduling, Bin packing assignment algorithm
for EDF, Myopic offline scheduling(MOS) algorithm, Focused addressing and bidding(FAB)
algorithm, Buddy strategy, Assignment with precedence conditions.
Unit III:
Programming Languages & Tools- Desired language characteristics,, data typing, control
structures, hierarchical decomposition, packages, run time error handling, Overloading and
genetics, Multitasking, Low level programming, Fex, Euclid, Run time support.
Unit IV:
Real time Communication-Communication media, network topologies. Protocols-
Contention based, Token based, Stop-and-Go, Polled bus, Hierarchical round robin, deadline
based.
Unit V:
Fault Tolerance Techniques- Fault, fault types, fault detection, fault and error containment,
hardware and software redundancy, time redundancy, information redundancy. Reversal checks,
Malicious or Byzantine failures, Integrated failure handling.
IT832 Image processing
Unit I:
Image representation, fundamental steps in image processing, image model. Sampling &
quantization. Neighbors of a pixel, connectivity and distance measures. Basic transformations and
perspective transformations. Two dimensional Fourier transform, Discrete Fourier transform and
their properties. Fast Fourier transform, Walsh Transform, Hadamard transform and Discrete
Cosine transform.
Unit II:
Image Enhancement: Intensity transformations, histogram processing, Image subtraction,
image averaging, Spatial filtering-smoothing and sharpening filters, frequency domain filtering
methods-low pass filtering, high pass filtering, median filtering.
Unit III:
Image compression: Redundancy and its types. Image compression model, variable
length coding, bit plane coding, constant area coding, run length coding, lossless and lossy
predictive coding, transform coding.
Unit IV:
Image restoration and Segmentation: Degradation model, effect of diagonalisation on
degradation, algebraic approach. Detection of discontinuities by point, line and edge detection.
Edge linking, graph theoretic techniques, thresholding techniques, region oriented segmentation.
Unit V:
Representation & Description: Chain codes, polygonal approximations, signatures,
boundary segments, skeleton, boundary descriptors, shape descriptors regional descriptors, image
morphology-dilation, erosion, opening, closing, thickening, thinning, skeleton, pruning,, hit or miss
transform.
IT 833 Artificial Intelligence
Unit I:
Meaning and definition of artificial intelligence, Various types of production systems,
Characteristics of production systems, Study and comparison of breadth first search and depth first
search. Techniques, other Search Techniques like hill Climbing, Best first Search. A* algorithm,
AO* algorithms etc, and various types of control strategies.
Unit II:
Knowledge Representation, Problems in representing knowledge, knowledge
representation using propositional and predicate logic, comparison of propositional and predicate
logic, Resolution, refutation, deduction, theorem proving, inferencing, monotonic and nonmonotonic
reasoning.
Unit III:
Probabilistic reasoning, Baye's theorem, semantic networks, scripts, schemas, frames,
conceptual dependency, fuzzy logic, forward and backward reasoning.
Unit IV:
Game playing techniques like minimax procedure, alpha-beta cut-offs etc, planning, Study
of the block world problem in robotics, Introduction to understanding and natural languages
processing.
Unit V:
Introduction to learning, Various techniques used in learning, introduction to neural
networks, applications of neural networks, common sense, reasoning, some example of expert
systems.
IT840-Data Mining & Warehousing
Unit I:
Data Warehousing: Need for data warehousing , Basic elements of data warehousing,
Data Mart, Data Warehouse Architecture, extract and load Process, Clean and Transform data,
Star ,Snowflake and Galaxy Schemas for Multidimensional databases, Fact and dimension data,
Partitioning Strategy-Horizontal and Vertical Partitioning.
Unit II:
Data Warehouse and OLAP technology, Multidimensional data models and different OLAP
Operations, OLAP Server: ROLAP, MOLAP, Data Warehouse implementation ,Efficient
Computation of Data Cubes, Processing of OLAP queries, Indexing data.
Unit III:
Data Mining: Data Preprocessing ,Data Integration and Transformation, Data Reduction,
Discretizaion and Concept Hierarchy Generation , Basics of data mining, Data mining techniques,
KDP (Knowledge Discovery Process), Application and Challenges of Data Mining, Introduction of
Web Structure Mining, Web Usage Mining, Spatial Mining, Text Mining, Security Issue, Privacy
Issue, Ethical Issue.
Unit IV:
Mining Association Rules in Large Databases: Association Rule Mining, Single-
Dimensional Boolean Association Rules, Multi-Level Association Rule, Apriori Algorithm, Fp-
Growth Algorithm, Time series mining association rules, latest trends in association rules mining.
Unit V:
Classification and Clustering Distance Measures, Types of Clustering, K-Means Algorithm,
Decision Tree Induction, Bayesian Classification, Association Rule Based, Other Classification
Methods,
Prediction, Classifier Accuracy, Categorization of methods, Partitioning methods, Outlier Analysis.
IT841-Cyber law & Forensic
Unit I:
Cyber world: an overview, internet and online resources, security of information, digital
signature, intellectual property (IP), historical background of IP, IPR governance, National patent
offices, the world intellectual property organization (WIPO).
Unit II:
Introduction about the cyber space, cyber law, regulation of cyber space, scope of cyber
laws: ecommerce; online contracts; IPRs (copyright, trademarks and software patenting), etaxation;
e-governance and cyber crimes, cyber law in India with special reference to Information
Technology Act, 2000.
Unit III:
Introduction to computer and cyber crimes. Cyber crimes and related concepts, distinction
between cyber crimes and conventional crimes, Cyber criminals and their objectives. Kinds of
cyber crimes cyber stalking; cyber pornography, forgery and fraud, crime related to IPRs, cyber
terrorism; computer vandalism etc. Cyber forensics, computer forensics and the law, forensic
evidence, computer forensic tools.
Unit IV:
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.
Unit V:
Copyright issues in cyberspace: linking, framing, protection of content on web site,
international treaties, trademark issues in cyberspace: domain name dispute, cyber squatting,
uniform dispute resolution policy, computer software and related IPR issues.
IT842- Adhoc Network
Unit I
Introduction :Introduction-Fundamentals of Wireless Communication Technology, The
Electromagnetic Spectrum, GSM, GPRS, PCS, WLAN and UMTS, Components of Packet Radios,
Routing in PRNETs, Route calculation, Pacing techniques, Ad Hoc Wireless Networks,
Heterogeneity in Mobile Devices, Wireless Sensor Networks, Traffic Profiles, Types of Ad Hoc
Mobile Communications, Types of Mobile Host Movements, Challenges Facing Ad Hoc Mobile
Networks.
Unit II
Ad Hoc wireless MAC protocols- Introduction, Synchronous and asynchronous MAC
protocols, Problem in Ad Hoc channel access, Receiver-initiated and sender-initiated MAC
protocols, Existing Ad Hoc MAC protocols, Ad Hoc Routing Protocols- Introduction, Issues in
Designing a Routing Protocol for Ad Hoc Wireless Networks, Classifications of Routing Protocols:
Table-Driven Routing Protocols – Destination Sequenced Distance Vector (DSDV), Wireless
Routing Protocol (WRP), Cluster Switch Gateway Routing (CSGR), Source-Initiated On-Demand
Approaches - Ad Hoc On-Demand Distance Vector Routing (AODV), Dynamic Source Routing
(DSR), Temporally Ordered Routing Algorithm (TORA), Signal Stability Routing (SSR) Location-
Aided Routing (LAR), Power-Aware Routing (PAR), Zone Routing Protocol (ZRP).
Unit III
Multicast routing In Ad Hoc Networks : Introduction, Issues in Designing a Multicast
Routing Protocol, Operation of Multicast Routing Protocols, An Architecture Reference Model for
Multicast Routing Protocols, Classifications of Multicast Routing Protocols, Tree-Based Multicast
Routing Protocols, Mesh- Based Multicast Routing Protocols, Summary of Tree-and Mesh-Based
Protocols - Energy-Efficient Multicasting, Multicasting with Quality of Service Guarantees,
Application Dependent Multicast Routing, Comparisons of Multicast Routing Protocols.
Unit IV
Transport Layer, Security Protocols : Introduction, Issues in Designing a Transport Layer
Protocol for Ad Hoc Wireless Networks, Design Goals of a Transport Layer Protocol for Ad Hoc
Wireless Networks, Classification of Transport Layer Solutions, TCP Over Ad Hoc Wireless
Networks, Other Transport Layer Protocols for Ad Hoc Wireless Networks, Security in Ad Hoc
Wireless Networks, Network Security Requirements, Issues and Challenges in Security
Provisioning, Network Security Attacks, Key Management, Secure Routing in Ad Hoc Wireless
Networks.
Unit V
QoS and Energy Management : Introduction, Issues and Challenges in Providing QoS in
Ad Hoc Wireless Networks, Classifications of QoS Solutions, MAC Layer Solutions, Network Layer
Solutions, QoS Frameworks for Ad Hoc Wireless Networks, Energy Management in Ad Hoc
Wireless Networks – Introduction, Need for Energy Management in Ad Hoc Wireless Networks,
Classification of Energy Management Schemes, Battery Management Schemes, Transmission
Power Management Schemes, System Power Management Schemes.
IT843 - Operation Research
Unit I:
Introduction to Linear Programming, Solution by Graphical and Simplex Method, Concept of
Degeneracy and Duality, Artificial Variable Techniques : Big-M Method, Two Phase Method ,
Solution of Transportation Problems by North-West Corner Method, Lowest Cost Entry Method,
Vogel’s Method, Non- Degenerate Basic Feasible Solution, Assignment Model
Unit II:
Integer Programming: Relationship to Linear Programming, Branch and Bound, Cutting
Plane Techniques: General Cutting Planes , Dynamic Programming: Introduction, Bellman’s
Principle of optimality, Applications of dynamic programming, Critical Path Method, PERT
Unit III:
Replacement, Introduction, Replacement of items that deteriorate with time when money
value is not counted and counted, Replacement of items that fail completely, group replacement.
Games Theory: Introduction, Minimax (maximin), Criterion and optimal strategy, Solution of games
with saddle points, Rectangular games without saddle points, 2 X 2 games, dominance principle–
m X 2 & 2 X n games.
Unit IV:
Inventory : Introduction , Single item – Deterministic models, Purchase inventory models
with one price break and multiple price breaks shortages are not allowed , Stochastic models
demand may be discrete variable or continuous variable, Instantaneous production. Instantaneous
demand and continuous demand and no set up cost.
Unit V:
Waiting Lines: Introduction, Single Channel, Poisson arrivals, exponential service times
with infinite population and finite population models, Multi channel, Poisson arrivals, exponential
service times with infinite population single channel Poisson arrivals: (M/M/1 : /FCFS), (M/M/1 :
N/FCFS), (M/Ek/1 : /FCFS), (M/M/S : /FCFS)
