Computer Engineering Semester 7


Computer Engineering Semester 7

Digital Signal Processing
Discrete Time Signal
1.1 Introduction to Digital Signal Processing, Discrete Time Signals,
Sampling and Reconstruction, Standard DT Signals, Concept of Digital
Frequency, Representation of DT signal using Standard DT Signals,
Signal Manipulations(shifting, addition, subtraction, multiplication),
Classification of Signals, Linear Convolution formulation(without
mathematical proof), Circular Convolution formulation(without
mathematical proof), Matrix Representation of Circular Convolution,
Linear by Circular Convolution. Auto and Cross Correlation formula
evaluation,

02 Discrete Time System
2.1 Introduction to Discrete Time System, Classification of DT Systems
(Linear/Non Linear, Causal/Non Causal, Time Invariant/Time Variant
Systems, Stable/ Unstable), BIBO Time Domain Stability Criteria. LTI
system, Concept of Impulse Response and Step Response.
2.2 Concept of IIR System and FIR System, Output of IIR and FIR DT
system using Time Domain Linear Convolution formula Method.

03 Discrete Fourier Transform
3.1 Introduction to DTFT, DFT, Relation between DFT and DTFT, Properties
of DFT without mathematical proof (Scaling and Linearity, Periodicity,
Time Shift and Frequency Shift, Time Reversal, Convolution Property
and Parsevals’ Energy Theorem). DFT computation using DFT properties.
3.2 Transfer function of DT System in frequency domain using DFT. Linear
and Circular Convolution using DFT. Response of FIR system calculation
in frequency domain using DFT.

04 Fast Fourier Transform
4.1 Radix-2 DIT-FFT algorithm, DIT-FFT Flowgraph for N=4, 6 & 8, InveFFT algorithm. Spectral Analysis using FFT, Comparison of complex and
real, multiplication and additions of DFT and FFT.
05 DSP Algorithms
5.1 Carls’ Correlation Coefficient Algorithm, Fast Circular Convolution
Algorithm, Fast Linear Convolution Algorithm, Linear FIR filtering
using Fast Overlap Add Algorithm and Fast Overlap Save Algorithm,

06 DSP Processors and Application of DSP
6.1 Need for Special architecture of DSP processor, Difference between DSP
processor & microprocessor, A general DSP processor TMS320C54XX
series, Case study of Real Time DSP applications to Speech Signal
Processing and Biomedical Signal Processing.

Term Work:
· Term work shall consist of minimum 08 assignments and course project.
· Journal must include at least 1 assignment on each module and two quiz.
· The final certification and acceptance of term work ensures that satisfactory performance
of laboratory work and minimum passing marks in term work.
The distribution of marks for term work shall be as follows:
· Laboratory work (experiments): …………..……….. (15) Marks.
· Assignment:……………………………………..…… (05) Marks.
· Attendance (Theory+ Practical)……………………. (05) Marks
TOTAL: ……………………………………………………. (25) Marks.
Text Books :
1. Ashok Ambardar, ‘Digital Signal Processing’, Cengage Learning, 2007,
ISBN : 978-81-315-0179-5.
2. Emmanuel C. Ifeachor, Barrie W. Jervis, “Digital Signal Processing: A Practical Approach”,
Pearson Education ISBN 0-201-59619- 9
3. S. Salivahanan, A. Vallavaraj, C. Gnanapriya, ‘Digital Signal Processing’ TataMcgraw Hill
Publication First edition (2010). ISBN 978-0-07-066924-6.
4. Avtar Signh, S.Srinivasan,”Digital Signal Processing’, Thomson Brooks/Cole,
ISBN : 981-243-254-4
 
Cryptography and System Security
Introduction
1.1 Security Attacks, Security Goals, Computer criminals, Methods of
defense, Security Services, Security Mechanisms

02 Basics of Cryptography
2.1 Symmetric Cipher Model, Substitution Techniques, Transportation
Techniques, Other Cipher Properties- Confusion, Diffusion, Block and
Stream Ciphers.

03 Secret Key Cryptography
3.1 Data Encryption Standard(DES), Strength of DES, Block Cipher
Design Principles and Modes of Operations, Triple DES, International
Data Encryption algorithm, Blowfish, CAST-128.

04 Public Key Cryptography
4.1 Principles of Public Key Cryptosystems, RSA Algorithm, Diffie-
Hellman Key Exchange

05 Cryptographic Hash Functions
5.1 Applications of Cryptographic Hash Functions, Secure Hash
Algorithm, Message Authentication Codes – Message Authentication
Requirements and Functions, HMAC, Digital signatures, Digital
Signature Schemes, Authentication Protocols, Digital Signature
Standards.

06 Authentication Applications
6.1 Kerberos, Key Management and Distribution, X.509 Directory
Authentication service, Public Key Infrastructure, Electronic Mail
Security: Pretty Good Privacy, S/MIME.7.1 Program Security
Secure programs, Nonmalicious Program Errors, Malicious Software –
Types, Viruses, Virus Countermeasures, Worms, Targeted Malicious
Code, Controls against Program Threats.
7.2 Operating System Security
Memory and Address protection, File Protection Mechanism, User
Authentication.
7.3 Database Security
Security Requirement, Reliability and Integrity, Sensitive data, Inference,
Multilevel Databases
7.4 IDS and Firewalls
Intruders, Intrusion Detection, Password Management, Firewalls-
Characteristics, Types of Firewalls, Placement of Firewalls, Firewall
Configuration, Trusted systems.

08 8.1 IP Security
Overview, Architecture, Authentication Header, Encapsulating Security
Payload, Combining security Associations, Internet Key Exchange, Web
Security: Web Security Considerations, Secure Sockets Layer and
Transport Layer Security, Electronic Payment.
8.2 Non-cryptographic protocol Vulnerabilities
DoS, DDoS, Session Hijacking and Spoofing, Software Vulnerabilities-
Phishing, Buffer Overflow, Format String Attacks, SQL Injection.

Term Work:
Term work should consist of at least 10experiments, 2 assignments based on above theory
syllabus.
The final certification and acceptance of term work ensures that satisfactory performance of
laboratory work and minimum passing marks in term work.
The distribution of marks for term work shall be as follows:
· Laboratory work (experiments): …………..……….. (15) Marks.
· Assignment:……………………………………..…… (05) Marks.
· Attendance (Theory+ Practical)……………………. (05) Marks
TOTAL: ……………………………………………………. (25) Marks.
Theory Examination:
1. Question paper will comprise of total 6 questions, each of 20 Marks.
2. Only 4 questions need to be solved.
3. Question 1 will be compulsory and based on maximum part of the syllabus.
4. Remaining questions will be mixed in nature (for example suppose Q.2 has part (a) from
module 3 then part (b) will be from any module other than module 3)
In question paper, weightage of each module will be proportional to number of respective
lecture hours as mentioned in the syllabus.
Text Books:
1. Cryptography and Network Security: Principles and Practice 5th edition, William
Stallings, Pearson.
2. Network Security and Cryptography 2nd edition, Bernard Menezes, Cengage Learning.
3. Cryptography and Network, 2nd edition, Behrouz A Fourouzan, Debdeep
Mukhopadhyay, TMH.

 

Artificial Intelligence
Introduction to Artificial Intelligence
1.1 Introduction , History of Artificial Intelligence, Intelligent
Systems: Categorization of Intelligent System, Components
of AI Program, Foundations of AI, Sub-areas of AI,
Applications of AI, Current trends in AI.

02 Intelligent Agents
2.1 Agents and Environments, The concept of rationality, The
nature of environment, The structure of Agents, Types of
Agents, Learning Agent.

03 Problem solving
3.1 Solving problem by Searching : Problem Solving Agent,
Formulating Problems, Example Problems.
3.2 Uninformed Search Methods: Breadth First Search (BFS),
Depth First Search (DFS) , Depth Limited Search, Depth
First Iterative Deepening(DFID), Informed Search Methods:
Greedy best first Search ,A* Search , Memory bounded
heuristic Search.
3.3 Local Search Algorithms and Optimization Problems: Hillclimbing
search Simulated annealing, Local beam search,Genetic algorithms.
3.4 Adversarial Search: Games, Optimal strategies, The
minimax algorithm , Alpha-Beta Pruning.
04 Knowledge and Reasoning
4.1 Knowledge based Agents, The Wumpus World, The
Propositional logic, First Order Logic: Syntax and Semantic,
Inference in FOL, Forward chaining, backward Chaining.
4.2 Knowledge Engineering in First-Order Logic, Unification,
Resolution, Introduction to logic programming (PROLOG).
4.3 Uncertain Knowledge and Reasoning:
Uncertainty, Representing knowledge in an uncertain
domain, The semantics of belief network, Inference in belief
network.

05 Planning and Learning
5.1The planning problem, Planning with state space search,
Partial order planning, Hierarchical planning, Conditional
Planning.
5.2 Learning: Forms of Learning, Inductive Learning, Learning
Decision Tree.
5.3 Expert System: Introduction, Phases in building Expert
Systems, ES Architecture, ES vs Traditional System.

06 Applications
6.1 Natural Language Processing(NLP), Expert Systems.

Term Work:
The distribution of marks for term work shall be as follows:
· Laboratory work (experiments/case studies): ………….. (15) Marks.
· Assignment:………..………………………………… (05) Marks.
· Attendance ………………………………………. (05) Marks
TOTAL: ……………………………………………………. (25) Marks.
Text Books:
1. Stuart J. Russell and Peter Norvig, “Artificial Intelligence A Modern Approach “Second Edition”
Pearson Education.
2. Saroj Kaushik “Artificial Intelligence” , Cengage Learning.
3. George F Luger “Artificial Intelligence” Low Price Edition , Pearson Education., Fourth edition.
 
Advanced Algorithms
 
Introduction
1.1 Asymptotic notations Big O, Big Q,Big W,o ,w
notations ,Proofs of master theorem, applying
theorem to solve problems

02 Advanced Data Structures
2.1 Red-Black Trees: properties of red-black trees , Insertions ,
Deletions
2.2 B-Trees and its operations
2.3 Binomial Heaps: Binomial trees and binomial heaps, Operation
on Binomial heaps

03 Dynamic Programing
3.1 matrix chain multiplication, cutting rod problem and its analysis

04 Graph algorithms
4.1 Bellman ford algorithm, Dijkstra algorithm, Johnson’s All pair
shortest path algorithm for sparse graphs

05 Maximum Flow
5.1 Flow networks , the ford Fulkerson method ,max bipartite
matching , push Relabel Algorithm , The relabel to front
algorithm

06 Linear Programing
6.1 Standard and slack forms, Formulating problems as linear
programs, simplex algorithm, Duality, Initial basic feasible
solution

07 Computational Ggeometry
7.1 Line Segment properties, Determining whether any pair of
segment intersects, finding the convex hull, Finding the closest
pair of points.

Term Work:
Term work should consist of at least 6 experiments, 2 assignments based on above theory
syllabus.
The final certification and acceptance of term work ensures that satisfactory performance of
laboratory work and minimum passing marks in term work.
The distribution of marks for term work shall be as follows:
· Laboratory work (experiments): …………..……….. (15) Marks.
· Assignment:……………………………………..…… (05) Marks.
· Attendance (Theory+ Practical)……………………. (05) Marks
TOTAL: ……………………………………………………. (25) Marks
Text Books:
1. T.H. Coreman , C.E. Leiserson, R.L. Rivest, and C. Stein, “Introduction to algorithms”,2nd
edition , PHI publication 2005
2. Ellis Horowitz , Sartaj Sahni , S. Rajsekaran. “Fundamentals of computer algorithms”
University press

 

Image Processing
Digital Image and Video Fundamentals
1.1 Introduction to Digital Image, Digital Image Processing System,
Sampling and Quantization, Representation of Digital Image,
Connectivity, Image File Formats : BMP, TIFF and JPEG. Colour Models
(RGB, HSI, YUV) Introduction to Digital Video, Chroma Sub-sampling,
CCIR standards for Digital Video

02 Image Enhancement
2.1 Gray Level Transformations, Zero Memory Point Operations, Histogram
Processing, Neighbourhood Processing, Spatial Filtering, Smoothing and
Sharpening Filters. Homomorphic Filtering

03 Image Segmentation and Representation
3.1 Detection of Discontinuities, Edge Linking using Hough Transform,
Thresholding, Region based Segmentation, Split and Merge Technique,
Image Representation and Description, Chain Code, Polygonal
Representation, Shape Number, Moments.

04 Image Transform
4.1 Introduction to Unitary Transform, Discrete Fourier Transform(DFT),
Properties of DFT, Fast Fourier Transform(FFT), Discrete Hadamard
Transform(DHT), Fast Hadamard Transform(FHT), Discrete Cosine
Transform(DCT), Discrete Wavelet Transform(DWT),

05 Image Compression
5.1 Introduction, Redundancy, Fidelity Criteria,
5.2 Lossless Compression Techniques : Run Length Coding, Arithmetic
Coding, Huffman Coding, Differential PCM,5.3 Lossy Compression Techniques: Improved Gray Scale Quantization,
Vector Quantization, JPEG, MPEG-1.
06 Binary Image Processing
6.1 Binary Morphological Operators, Hit-or-Miss Transformation, Boundary
Extraction, Region Filling, Thinning and Thickening, Connected
Component Labeling, Iterative Algorithm and Classical Algorithm

Term Work:
Term work should consist of at least 08 experiments.
Journal must include at least 1 assignment on each module and two quiz.
The final certification and acceptance of term work ensures that satisfactory performance of
laboratory work and minimum passing marks in term work.
The distribution of marks for term work shall be as follows:
· Laboratory work (experiments): …………..……….. (15) Marks.
· Assignment:……………………………………..…… (05) Marks.
· Attendance (Theory+ Practical)……………………. (05) Marks
TOTAL: ……………………………………………………. (25) Marks.
Text Books :
1. Rafel C. Gonzalez and Richard E. Woods, ‘Digital Image Processing’, Pearson Education Asia,
Third Edition, 2009,
2. S. Jayaraman, E.Esakkirajan and T.Veerkumar, “Digital Image Processing” TataMcGraw Hill
Education Private Ltd, 2009,
3. Anil K. Jain, “Fundamentals and Digital Image Processing”, Prentice Hall of India Private Ltd,
Third Edition
4. S. Sridhar, “Digital Image Processing”, Oxford University Press, Second Edition, 2012.
5. Robert Haralick and Linda Shapiro, “Computer and Robot Vision”, Vol I, II, Addison
Wesley, 1993.
 
Software Architecture
 
Basic Concepts
1.1 Concepts of Software Architecture
1.2 Models.
1.3 Processes.
1.4 Stakeholders
03
02 Designing Architectures
2.1 The Design Process.
2.2 Architectural Conception.
2.3 Refined Experience in Action: Styles and Architectural Patterns.
2.4 Architectural Conception in Absence of Experience.

03 Connectors
3.1 Connectors in Action: A Motivating Example.
3.2 Connector Foundations.
3.3 Connector Roles.
3.4 Connector Types and Their Variation Dimensions.
3.5 Example Connectors.

04 Modeling
4.1 Modeling Concepts.
4.2 Ambiguity, Accuracy, and Precision.
4.3 Complex Modeling: Mixed Content and Multiple Views.
4.4 Evaluating Modeling Techniques.
4.5 Specific Modeling Techniques.

05 Analysis
5.1 Analysis Goals.
5.2 Scope of Analysis.
5.3 Architectural Concern being Analyzed.
5.4 Level of Formality of Architectural Models.5.5 Type of Analysis.
5.6 Analysis Techniques.
06 Implementation and Deployment
6.1 Concepts.
6.2 Existing Frameworks.
6.3 Software Architecture and Deployment.
6.4 Software Architecture and Mobility.

07 Conventional Architectural styles
7.1 Pipes and Filters
7.2 Event- based, Implicit Invocation
7.3 Layered systems
7.4 Repositories
7.5 Interpreters
7.6 Process control

08 Applied Architectures and Styles
8.1 Distributed and Networked Architectures.
8.2 Architectures for Network-Based Applications.
8.3 Decentralized Architectures.
8.4 Service-Oriented Architectures and Web Services.

09 Designing for Non-Functional Properties
9.1 Efficiency.
9.2 Complexity.
9.3 Scalability and Heterogeneity.
9.4 Adaptability.
9.5 Dependability.

10 Domain-Specific Software Engineering
10.1 Domain-Specific Software Engineering in a Nutshell.
10.2 Domain-Specific Software Architecture.
10.3 DSSAs, Product Lines, and Architectural Styles.

Term Work:
The distribution of marks for term work shall be as follows:
· Laboratory work (experiments):…………………….. (20) Marks.
· Attendence:…….……………………………………… (05) Marks.
TOTAL: ……………………………………………………. (25) Marks.
Text Books:
1. “Software Architecture: Foundations, Theory, and Practice” by Richard N. Taylor,
Nenad Medvidovic, Eric Dashofy, ISBN: 978-0-470-16774-8
2. M. Shaw: Software Architecture Perspectives on an Emerging Discipline, Prentice-Hall.
3. Len Bass, Paul Clements, Rick Kazman: Software Architecture in Practice, Pearson.
Soft Computing
Introduction to Soft Computing
1.1 Soft computing Constituents, Characteristics of Neuro
Computing and Soft Computing, Difference between Hard
Computing and Soft Computing, Concepts of Learning and
Adaptation.

02 Neural Networks
2.1 Basics of Neural Networks:
Introduction to Neural Networks, Biological Neural
Networks, McCulloch Pitt model,
2.2 Supervised Learning algorithms:
Perceptron (Single Layer, Multi layer), Linear separability,
Delta learning rule, Back Propagation algorithm,
2.3 Un-Supervised Learning algorithms: Hebbian Learning,
Winner take all, Self Organizing Maps, Learning Vector
Quantization.
Fuzzy Set Theory
3.1 Classical Sets and Fuzzy Sets, Classical Relations and Fuzzy
Relations, Properties of membership function, Fuzzy
extension principle, Fuzzy Systems- fuzzification,
defuzzification and fuzzy controllers.

04 Hybrid system
4.1 Introduction to Hybrid Systems, Adaptive Neuro Fuzzy
Inference System(ANFIS).

05 Introduction to Optimization Techniques
5.1 Derivative based optimization- Steepest Descent, Newton
method.
5.2 Derivative free optimization- Introduction to Evolutionary
Concepts.

06 Genetic Algorithms and its applications:
6.1 Inheritance Operators, Cross over types, inversion and
Deletion, Mutation Operator, Bit-wise Operators,
Convergence of GA, Applications of GA.

Term Work:
The distribution of marks for term work shall be as follows:
· Laboratory work (experiments/case studies): ………….. (15) Marks.
· Assignments:…….…………………………………… (05) Marks.
· Attendance ………………………………………. (05) Marks
TOTAL: ……………………………………………………. (25) Marks.
Text Books:
1. Timothy J.Ross “Fuzzy Logic With Engineering Applications” Wiley.
2. S.N.Sivanandam, S.N.Deepa “Principles of Soft Computing” Second Edition, Wiley
Publication.
3. S.Rajasekaran and G.A.Vijayalakshmi Pai “Neural Networks, Fuzzy Logic and Genetic
Algorithms” PHI Learning.
4. J.-S.R.Jang “Neuro-Fuzzy and Soft Computing” PHI 2003.
5. Jacek.M.Zurada “Introduction to Artificial Neural Sytems” Jaico Publishing House.
Enterprise Resource Planning and Supply Chain
Management (ERP & SCM)
Introduction
1.1 What is an Enterprize, Introduction to ERP, Need for ERP,
Structure of ERP, Scope and Benefits, Typical business
processes.

02 ERP and Technology
2.1 ERP and related technologies, Business Intelligence, E-business
and E-commerce, Business Process Reengineering,

03 ERP and Implementation
3.1 ERP implementation and strategy, Implementation Life cycle,
Pre-implementation task, requirement definition , implementation
methodology.

04 ERP Business Modules
4.1 Modules: Finance, manufacturing, human resources, quality
management, material management, marketing. Sales distribution
and service.

05 Extended ERP
5.1 Enterprise application Integration (EAI), open source ERP, cloud
ERP.

Supply Chain Management (SCM)
06 Introduction and strategic decisions in SCM6.1 Introduction to SCM, Generic Types of supply chain, Major
Drivers of Supply chain, Strategic decisions in SCM, Business
Strategy, CRM strategy, SRM strategy, SCOR model.
07 Information Technology in SCM
7.1 Types of IT Solutions like Electronic Data Inter change (EDI),
Intranet/ Extranet, Data Mining/ Data Warehousing and Data
Marts, E-Commerce, E- Procurement, Bar coding, RFID, QR
code.

08 Mathematical modelling for SCM
8.1 Introduction, Considerations in modelling SCM systems,
Structuring the logistics chain, overview of models: models on
transportation problem, assignment problem, vehicle routing
problem, Model for vendor analysis, Make versus buy model.

09 Agile Supply Chain
9.1 Introduction, Characteristics of Agile Supply Chain, Achieving
Agility in Supply Chain.

10 Cases of Supply Chain
10.1 Cases of Supply Chain like, News Paper Supply Chain, Book
Publishing, Mumbai Dabbawala, Disaster management, Organic
Food, Fast Food.

Term Work:
The distribution of marks for term work shall be as follows:
· Mini project:……………………………….………… (20) Marks.
· Attendance …………………………………………. (05) Marks
TOTAL: ……………………………………………………. (25) Marks.
Text Books:
1. Enterprise Resource Planning : concepts & practices, by V.K. Garg & N.K.
Venkatakrishnan ; PHI.
2. Supply Chain Management Theories & Practices: R. P. Mohanty, S. G. Deshmukh, –
Dreamtech Press.
3. ERP Demystified: II Edition, by Alexis Leon,McGraw Hill .
4. Enterprise wide resource planning: Theory & practice: by Rahul Altekar,PHI.
Computer Simulation and Modeling
Introduction to Simulation.
Simulation Examples.
General Principles
15
02 Statistical Models in simulation.
Queuing Models

03 Random Number Generation.
Testing random numbers (Refer to Third edition)
Random Variate Generation: Inverse transform technique,
Direct Transformation for the Normal Distribution,
Convolution Method, Acceptance-Rejection Technique (only Poisson
Distribution).Analysis of simulation data : Input Modeling ,Verification, Calibration
and Validation of Simulation , Models , Estimation of absolute
performance.

05 Application : Case study on 1. Processor and Memory simulation
2. Manufacturing & Material handling

Text Books:
Discrete Event System Simulation; Third Edition, Jerry Banks, John Carson, Barry Nelson,
and David M. Nicol, Prentice-Hall
Discrete Event System Simulation; Fifth Edition, Jerry Banks, John Carson, Barry Nelson,
and David M. Nicol, Prentice-Hall
Term work:
Laboratory work: 10 marks
Mini Simulation Project presentation: 10 marks
Attendance : 5 marks
Network threats and attacks Laboratory
1.1 Title: Study the use of network reconnaissance tools like WHOIS, dig, traceroute,
nslookup to gather information about networks and domain registrars.
Objective: Objective of this module to how to gather information about the networks by
using different n/w reconnaissance tools.
Scope: Network analysis using network based tools
Technology: Networking
02 2.1 Title: Study of packet sniffer tools like wireshark, ethereal, tcpdump etc. You
should be able to use the tools to do the following
1. Observer performance in promiscuous as well as non-promiscous mode.
2. Show that packets can be traced based on different filters.
Objective: Objective of this module is to observer the performanance in promiscuous &
non-promiscous mode & to find the packets based on different filters.
Scope: Packet grapping, message and protocol analysis
Technology: Networking
03 3.1 Title: Download and install nmap. Use it with different options to scan open ports,
perform OS fingerprinting, do a ping scan, tcp port scan, udp port scan, etc.
Objective: objective of this module to learn nmap installation & use this to scan
different ports.
Scope: used for ip spoofing and port scanning
Technology: Networking4.1 Title: Detect ARP spoofing using open source tool ARPWATCH.
Objective: Objective of the module to find ARP spoofing using open source.
Scope: Ip spoofing using arp packaging tool
Technology: Networking
05 5.1 Title: Use the Nessus tool to scan the network for vulnerabilities.
Objective: Objective of the module is scan system and network analysis.
Scope: It used for system analysis, security and process analysis
Technology: Networking
06 6.1 Title: Implement a code to simulate buffer overflow attack.
Objective: Objective of the module Is to check buffer overflow in an NS2 environment
Scope: It uses to analyse memory overflow attack
Technology: Networking
07 7.1 Title: Set up IPSEC under LINUX
Objective: Objective of the module for implementing security vulnerabilities
Scope: to study different ipsec tools.
Technology: Networking
08 8.1 Title: Install IDS (e.g. SNORT) and study the logs.
Objective: Simulate intrusion detection system using tools such as snort
Scope: It is used for intrusion detection system vulnerability scans
Technology: Networking 9.1 Title: Use of iptables in linux to create firewalls.
Objective: To study how to create and destroy firewall security parameters.
Scope: system security and network security
Technology: Networking
10 10.1 Title: Mini project
Objective: To implement Networking concepts
Scope: To understand Network & system tools
Technology: Networking
Term Work:
The distribution of marks for term work shall be as follows:
· Lab Assignments:……………………………………………….. (10)
· Mini project:……………………………….………… (10) Marks.
· Attendance …………………………………………. (05) Marks
TOTAL: ……………………………………………………. (25) Marks
No comments yet.

Leave a Reply

Powered by WordPress. Designed by Woo Themes