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School of Computing Science and Engineering Department of Computer Science and Engineering

Document Reference Revision No. / Date Prepared By Approved By

SUN/SOCSE/COMP/UG/CSF/31/08/18 R0 / 31 August 2018

B. Tech CSE (with Specialization in Cyber Security and Forensics)

Semester – VII

CIA: Continuous Internal Assessment

L: Theory Lecture

T: Tutorial

P: Practical

TH: Theory Exam.

#: Internship for 15 days.

*: Oral Examination

UC: University Core

PC: Programme Core

PE: Programme Elective

CIA Weightage Description

CIA 1 10% Home Assignment

CIA 2 20% Mid-Term Exam (MTE)

CIA 3 10% Seminar Presentation

CIA 4 10% Research Based Activity

TOTAL 50%

Open Elective II:

1. Cloud Computing and Virtualization(YCF O03)

2. Cyber Laws (YCFO04)

3. Introduction on Intellectual Property to Engineers and Technologists(YCFO05)

Note: YCF714 - After 6

th Semester Maximum of Five weeks, Student must submit a report for the same.

Sr.

No. Core

Course

Code Course Name

Teaching Scheme

(Hrs./Week)

Examination Scheme

Total Marks

L T P C

Formative

Assessment

CIA

Summative

Assessment

ESE

Course Lab Course Lab

1 PC YCF701 Object Oriented Analysis and

Design 3 -- -- 3 50 -- 50 -- 100

2 PC YCF702 Digital Forensics 3 -- -- 3 50 -- 50 -- 100

3 PC YCF703

Information Security Audit and

Monitoring and management

practices

3 -- -- 3 50 -- 50 -- 100

4 PC YCFO__ Open Elective II 3 -- -- 3 50 -- 50 -- 100

5 PC YCF711 Object Oriented Analysis and

DesignLab -- -- 4 2 -- 25 -- 25 50

6 PC YCF712 Digital Forensics Lab -- -- 4 2 -- 25 -- 25 50

7 UC YCF713 Dissertation Stage I -- -- 8 4 -- 50 -- 50 100

8 UC YCF714 Industry Internship -- 2 -- 2 -- 50 -- -- 50

TOTAL 12 02 16 22 200 150 200 100 650




Year: Fourth Year Semester – VII

Course: Object Oriented Analysis and Design Course Code: YCF701

Teaching

Scheme

(Hrs. /Week)

Continuous Internal Assessment (CIA) End Semester

Examination Total

L T P C CIA-1 CIA-2 CIA-3 CIA-4 Lab Theory Lab

3 - - 3 10 20 10 10 -- 50 -- 100

Max. Time, End Semester Exam (Theory) - 03 Hrs. End Semester Exam (Lab) – 00 Hrs.

Prerequisites:

Software Engineering

Objectives:

The course will enables students to:-

1 To Introduce various designing techniques and methods for object oriented

2 Performance analysis with real time system

3 Demonstrate a familiarity with object oriented data and system.

4 To give clear idea on implementing design with UML diagram like state diagram, activity

diagram, use case diagram etc.

Unit

No Details Hours

1

Module 1: Introduction, Object orientation, OODevelopment, OO themes,

Modeling as a design technique, Class Modeling. 4

Module 2:Abstraction, The three models, Object and classconcepts, Link and

association concepts, Generalization &Inheritance, Navigation of class models. 4

2

Module 1: Advanced object and class concepts, Association Ends, N-

aryassociation, Aggregation, Abstract classes, Multiple inheritance, 4

Module 2:Metadata, Reification, Constraints, Derived data, Packages,State

Modeling: Events, States, Transitions and Conditions, State diagrams, State

diagram behavior.

3

3

Module 1: Nested state diagram, Signal Generalization, Nested states,

Concurrency, Relation of class and state models, Use case model. 4

Module 2: Sequence models, Activity models, Use case relationships, Procedural

sequence model, Special constructs for activitymodels. 4

4

Module 1:Development stages, Development life cycle, Devising a

systemconcepts, Elaborating a concepts. 4

Module 2:, Preparing a problemstatements, Overview of analysis, Domain class

models, Domainstate model, Domain Interaction model. 3

5

Module 1:Overview of System Design, EstimatingPerformance, Making a reuse

plan, Breaking a system into subsystems, Identifying Concurrency, Allocation

ofsubsystems, Management of data storage, Handling globalresources, Choosing a

software control strategy.

4




Module 2:Handlingboundary conditions, Architectureof the ATM

system.Realizing the use cases, Designing algorithms recursing Downwards,

Refactoring, DesignOptimization, Reification of behavior, Organizing a class

design, ATM examples.

4

Outcomes:

On completion of the course, student will be able to–

1 Describe Object Oriented Analysis and Design concepts and apply them to solve problems

2 Prepare Object Oriented Analysis and Design documents for a given problem using Unified

Modeling Language

Text Books

Blaha ,Rumbaugh:”Object Oriented Modeling and Design with UML”(2/e) Pearson Education.

Reference Book

1. Dathan ,Ramnath : “Object Oriented Analysis, Design &Implementation,”OUP.

2. McRobb& Farmer: “Object Oriented System Analysis &Design”McGraw Hill.

3. 3Booch, Rumbaugh& Jacobson: “The UML User guide”PearsonEducation.

4. Whitten & Bentley: “System Analysis & Design Methods”TataMcGraw Hill.

5. Booch: “Object Oriented Analysis & Design with Applications”,Pearson Education.

6. Visual modeling with Rational Rose and UML by Terry Quatrani, by Addison-Wesley

Professional.





Course: Digital Forensics Course Code: YCF702

Teaching

Scheme

(Hrs. /Week)


Examination Total


3 - - 3 10 20 10 10 -- 50 -- 100


Prerequisites:

Information Security, System Security

Objectives:


1 Demonstrate knowledge and comprehension ofbasic tools and techniques used in the field

of computer forensics sciences.

2 Demonstrate general knowledge and comprehension of digital forensic sciences as a

profession.

Unit

No Details Hours

1

Module 1: Computer Forensics Standard Procedure, Incident Verification, System identification, Recovery of

Erased and damaged data,

4

Module 2:Disk imaging and preservation, Data encryption and compression,

Automated search techniques,Forensic software 4

2

Module 1: Network Forensics and Internet Forensics Tracking network traffic, Reviewing Network Logs, Tools, Performing Live

Acquisitions, Order ofvolatility, Standard Procedure. Internet & World Wide Web

threats (Email, Chat-rooms, Search Engines,Hacking & illegal access, Obscene

and indecent transmission, Extortion & threats), Domain NameOwnership

Investigation, Reconstructing Past Internet Activities and Events, Email Forensics:

E-mailAnalysis, Email Forensics: Email Headers and Spoofing, Email Forensics:

Laws against Email Crime

4

Module 2:Messenger Forensics: AOL, Yahoo, MSN, and Chats, Browser

Forensics: Analyzing Cache and TemporaryInternet Files, Browser Forensics:

Cookie Storage and Analysis, Browser Forensics: Web BrowsingActivity

Reconstruction

3

3

Module 1: Forensic Investigation and Evidence Presentation, Legal aspects of

Digital Forensics Authorization to collect the evidence, Acquisition of evidence, Authentication of

the evidence, Analysisof the evidence, Reporting on the findings, Testimony.

4

Module 2:Laws & regulations - Information Technology Act,Giving evidence in

court 4




4

Module 1:Memory Forensics, Mobile Forensics & Steganography Memory Data Collection and Examination, Extracting and Examining Processes.

Collecting and AnalyzingCell Phone, PDA, Blackberry, iPhone, iPod, iPad,and

MP3 Evidence, Analyzing CD, DVD, Tape Drives, USB,Flash Memory, and other

Storage Devices

4

Module 2:Digital Camera Forensics, Reconstructing Users Activities,Recovering

and Reconstructing Deleted Data. Steganography Tools and Tricks, Data Hiding,

DataRecovery.

3

5

Module 1: Malware Analysis Analyzing Live Windows System for Malware, Analyzing Live Linux System for

Malware, AnalyzingPhysical and Process Memory Dumps for Malware,

Discovering and Extracting Malware from WindowsSystems,

4

Module 2: Discovering and Extracting Malware from Linux Systems, Rootkits

and Rootkit Detection andRecovery, Reverse Engineering Tools and Techniques 4

Outcomes:

At the end of the course, the student will

1 Understand the different data recovery standards.

2 Gain an insight into various digital storage devices.

3 Develop an understanding of various sources of digital evidences.

4 Analyze how to perform auditing.

Text Books

1. Digital Forensics (IBM ICE Publication)

Reference Book





Course: Information Security Governance, Audit, Monitoring

and Management Practices Course Code: YCF703

Teaching

Scheme

(Hrs. /Week)


Examination Total


3 - - 3 10 20 10 10 -- 50 -- 100


Prerequisites:

IT System Security, IT Application Security

Objectives:


1 Know different auditing methods

2 Various reporting techniques

3 Different tools and techniques available for information monitoring

4 Different tools and techniques available for information management

Unit

No Details Hours

1

Module 1: Accountability, Compliance, Audit Trails, Reporting timeline, Record

Retention, External Auditors. 4

Module 2: Laws Monitoring tools, Warning banner, Traffic analysis, Trend

analysis.. 4

2

Module 1: Customers and Legal Agreements, Rules of Engagement, Penetration

Testing Planning and Scheduling, Pre Penetration Testing Checklist, Information

Gathering, Vulnerability Analysis, External Penetration Testing, Internal Network

Penetration Testing, Penetration testing for Denial of Service, Password Cracking,

Social Engineering, Stolen Laptop, PDAs and Cell phones, Application, Physical

Security, Database, VoIP, VPN, War Dialing, Virus and Trojan Detection

4

Module 2:Log Management, File Integrity Checking,

Blue Tooth and Hand held Device, Telecommunication and Broadband

Communication, Email Security, Security Patches, Data Leakage, Penetration

Testing Deliverables and Conclusion, Penetration Testing Report and

Documentation Writing, Penetration Testing Report Analysis, Post Testing

Actions, Ethics of a Penetration Tester, Standards and Compliance.

Countermeasures.

3

3

Module 1: Information Security Governance, Tone at the Top, Tone at the Bottom,

Governance, Risk, and Compliance (GRC), the Compliance Dilemma.

Evolution of Information Security, Organization Historical Perspective,

4




Understand the External Environment, The Internal Company Culture, Prior

Security Incidents, Audits , Security Strategy Development Techniques, Security

Planning.

Module 2: History of the Security Leadership Role Is Relevant, The New Security

Officer, Mandate, Security Leader Titles, Techie versus Leader, The Security

Leaders Library, Security Leadership Defined, Security Leader Soft Skills, Seven

Competencies for Effective Security Leadership, Security Functions, Reporting

Model.

4

4

Module 1: Communication between the CEO, CIO, Other Executives, and CISO,

Building Grassroots Support through an Information Security Council. Risk in Our

Daily Lives, Accepting Organizational Risk, Just Another Set of Risks,

Management Owns theRisk Decision, Qualitative versus Quantitative Risk

Analysis, Risk Management Process, Risk Mitigation Options.

4

Module 2:Why Information Security Policies Are Important, Avoiding Shelfware,

Electronic Policy Distribution, Canned Security Policies, Policies, Standards,

Guidelines Definitions, an Approach for Developing Information Security,

Policies, Utilizing the Security Council for Policies, the Policy Review Process.

3

5

Module 1 Security Control Convergence, Security Control Methodology, Security

Assessment and Authorization Controls, Planning Controls, Risk Assessment

Controls, System and Services Acquisition Controls, Program Management

Controls.Access Control Controls, Audit and Accountability, Controls,

Identification and Authentication, System and Communications Protections.

4

Module 2:Awareness and Training Controls, Configuration Management Controls,

Contingency Planning Controls, Incident Response Controls, Maintenance

Controls, Media Protection Controls, Physical and Environmental Protection

Controls, Personnel Security Controls, System and Information Integrity Controls.

4

Outcomes:


1 Knows Various reporting techniques

2 Understands different tools and techniques available for information monitoring

3 Understands different tools and techniques available for information management

Text Books

1. Professional Ethics: R. Subramanian, Oxford University Press, 2015.

2. Ethics in Engineering Practice & Research, Caroline Whit beck, 2e, Cambridge University Press

2015.

Reference Book

1. Engineering Ethics, Concepts Cases: Charles E Harris Jr., Michael S Pritchard, Michael J

Rabins, 4e, Cengagelearning, 2015.

2. Business Ethics concepts & Cases: Manuel G Velasquez, 6e, PHI, 2008.





Course: Cloud Computing and Virtualization Course Code: YCFO03

Teaching

Scheme

(Hrs. /Week)


Examination Total


3 -- -- 3 10 20 10 10 -- 50 -- 100

Max. Time, End Semester Exam (Theory) -3Hrs. End Semester Exam (Lab) - 00Hrs.

Prerequisites:

Computer Network, Operating System

Objectives:

Students are able to:-

1 Analyze the components of cloud computing showing how business agility in an

organization can be created

2 Evaluate the deployment of web services from cloud architecture

3 Critique the consistency of services deployed from a cloud architecture

4 Compare and contrast the economic benefits delivered by various cloud models based on

application requirements, economic constraints and business requirements.

5 Critically analyze case studies to derive the best practice model to apply

when developing and deploying cloud based application

Unit

No Details Hours

1

Module 1:CLOUD COMPUTING FUNDAMENTALS

Cloud Computing definition, private, public and hybrid cloud. Cloud types;

IaaS,PaaS, SaaS. Benefits and challenges of cloud computing, public vs private

clouds, role of virtualization in enabling the cloud; Business Agility: Benefits

and challenges to Cloud architecture.

4

Module 2:Application availability, performance, security and disaster recovery;

next generation Cloud Applications. 4

2

Module 1:MANAGEMENT OF CLOUD SERVICES

Reliability, availability and security of services deployed from the cloud.

Performance and scalability of services, tools and technologies used to manage

cloud services deployment; Cloud Economics : CloudComputing infrastructures

available for implementing cloud based services.

3

Module 2:Economics of choosing a Cloud platform for an organization, based

on application requirements, economic constraints and business needs (e.g

Amazon, Microsoft and Google, Salesforce.com, Ubuntu and Redhat)

3

3

Module 1:CLOUD IT MODEL

Analysis of Case Studies when deciding to adopt cloud computing architecture.

How to decide if the cloud is right for your requirements.

4




Module 2:Cloud based service,applications and development platform

deployment soas to improve the total costof ownership (TCO) 4

4

Module 1:VIRTUALIZED DATA CENTER ARCHITECTURE

Cloud infrastructures; public, private, hybrid. Service provider interfaces; Saas,

Paas, Iaas.

3

Module 2:VDC environments; concept, planning anddesign, business continuity

and disaster recovery principles. Managing VDC and cloud environments and

infrastructures.

3

5

Module 1:SECURITY CONCEPTS

Confidentiality, privacy, integrity, authentication, non-repudiation, availability,

access control, defence in depth, least privilege,how these concepts apply in the

cloud, what these concepts mean and their importance in PaaS, IaaS and SaaS.

e.g. User authentication in the cloud.

4

Module 2:Cryptographic Systems- Symmetric

cryptography, stream ciphers, block ciphers, modesof operation, public-key

cryptography, hashing, digital signatures

4

Outcomes:

After completion of course students will-

1 Explain the core concepts of the cloud computing paradigm: how and why this paradigm

shift came about, the characteristics, advantages and challenges brought about by the

various models and services in cloud computing.

2 Discuss system, network and storage virtualization and outline their role in enabling the

cloud computing system model.

3 Illustrate the fundamental concepts of cloud storage and demonstrate their use in storage

systems such as Amazon S3 and HDFS.

4 Analyze various cloud programming models and apply them to solve problems on the

cloud.

Text Books

1. GautamShroff, “Enterprise Cloud Computing Technology Architecture Applications”,

Cambridge University Press; 1 edition,[ISBN: 978-0521137355], 2010.

Reference Book

1. Toby Velte, Anthony Velte, Robert Elsenpeter, “Cloud Computing, A Practical Approach”

McGraw-Hill Osborne Media; 1 edition [ISBN: 0071626948], 2009.

2. Dimitris N. Chorafas, “Cloud Computing Strategies”CRC Press; 1 edition [ISBN: 1439834539],

2010.

3. Tim Mather, SubraKumaraswamy, ShahedLatif, “Cloud Security and Privacy: An Enterprise

Perspective on Risks and Compliance”O'Reilly Media; 1 edition[ISBN: 0596802765],2009

4. Greg Schulz, “Cloud and Virtual Data Storage Networking”, Auerbach Publications [ISBN: 978-

1439851739], 2011.





Course: Cyber Laws Course Code: YCFO04

Teaching

Scheme

(Hrs. /Week)


Examination Total


3 -- -- 3 10 20 10 10 -- 50 -- 100

Max. Time, End Semester Exam (Theory) -3Hrs. End Semester Exam (Lab) - 2Hrs.

Prerequisites:

Digital Forensics

Objectives:


1 Understand various legal measures that can be taken against various cyber crimes.

2 Understand various types of illegal or punishable offenses that can be done through digital

media.

3 Understand punishments constituted in cyber laws related to various malpractices in digital

world.

Unit

No Details Hours

1

Module 1:Introduction to cyber law, Indian Judiciary system 3

Module 2:Digital Signature and Electronic Signature, Penalty and compensation for

damage to computer 4

2

Module 1:Tampering with computer source documents, punishment for sending offensive

messages through communication service. 3

Module 2:Punishment for dishonestly receiving stolen computer resources or

communication device. 5

3

Module 1: Identity theft, punishment for identity theft, punishment for cheating by

personation by using computer resources. 3

Module 2:Explanation of privacy, punishment for violation of privacy, punishment for

cyber terrorism. 4

4

Module 1:Punishment for publishing or transmitting obscene material in electronic form,

punishment for plagiarism. 4

Module 2:Punishment for publishing or transmitting of material

containing sexually explicit act 3

5

Module 1:Punishmentfor publishing or transmitting of material depicting children in

sexually explicitact 3

Module 2:Breach of confidentiality and privacy 4

Outcomes:

1 Students are able to distinguish between legal and illegal activities in cyber world.

2 Students are able to use digital signature to claim the originator’s identity for an electronic




document.

3 Students are able to state various punishments related to plagiarism or illegal possession of

digital information.

4 Students will be driven away from performing any cyber crime.

Text Books

Cyber Laws Online Leaning Material

Reference Book

--





Course: Introduction on Intellectual Properties to Course Code: YCFO05

Engineers and Technologists

Teaching

Scheme

(Hrs. /Week)


Examination Total


3 -- -- 3 10 20 10 10 -- 50 -- 100

Max. Time, End Semester Exam (Theory) -3Hrs. End Semester Exam (Lab)

Prerequisites:

Cyber Laws

Objectives:


1 Understand basics of intellectual properties and copyrights.

2 Distinguish patentable and non-patentable inventions.

3 Understand industrial design basics and trademark basics.

4 Understand the infringement of copyright or trademark.

Unit

No Details Hours

1 Module 1: Basics of intellectual properties, introduction to law, theories of IP. 3

Module 2:Different forms of IP and application of thory. 4

2 Module 1:Patent Basics, Patent Ability criteria 4

Module 2:Non Patentable inventions, Prier art search, Patent filling procedure 4

3 Module 1: Patent Prosecution, International Patents 3

Module 2:Patent infringement, Patent management 4

4 Module 1:Utility module protection, copyright basics, copy right registration 4

Module 2:Copyright infringement and fair use, Copy right in digital media 4

5 Module 1:Industrial design basics, Industrial design registration 4

Module 2:Trademark basics, IC layout design 4

Outcomes:

1 Students are able to understand and use patent law and how patents are prosecuted and

enforced.

2 Students are able to comprehend complex intellectual property scenario.

3 Students are able to state criteria that determine infringement and law against it.

4 Students will be able to draft patent application.

5 Students will understand the importance of intellectual property laws in engineering and

related environment.

Text Books




1. Fundamentals of IP for engineers: K. Bansal and P. Bansal

2. Intellectual Property Rights: Deborah, E. Bauchoux. Cengage Learning

Reference Book

Intellectual Property Right- Unleashing the knowledge economy: PrabuddhaGanguli, TMH Publ.





Course: Object Oriented Analysis and DesignLab Course Code: YCF711

Teaching

Scheme

(Hrs. /Week)


Examination Total


-- -- 4 2 -- -- -- -- 25 -- 25 50

Max. Time, End Semester Exam (Theory) -00 Hrs. End Semester Exam (Lab) – 03 Hrs.

Prerequisites:


Objectives:


1 To Introduce various designing techniques and methods for object oriented

2 Performance analysis with real time system

3 Demonstrate a familiarity with object oriented data and system.

4 To give clear idea on implementing design with UML diagram like state diagram, activity

diagram, use case diagram etc.

Guidelines for Assessment

Continuous assessment of laboratory work is done based on overall performance and lab assignments

performance of student. Each lab assignment assessment will assign grade/marks based on parameters

with appropriate weightage. Suggested parameters for overall assessment as well as each lab assignment

assessment include- timely completion, performance, innovation, efficient codes, punctuality and

neatness.

Guidelines for Laboratory Conduction

The instructor is expected to frame the assignments by understanding the prerequisites, technological

aspects, utility and recent trends related to the topic. The assignment framing policy need to address the

average students and inclusive of an element to attract and promote the intelligent students. The

instructor may set multiple sets of assignments and distribute among batches of students. It is

appreciated if the assignments are based on real world problems/applications. Encourage students for

appropriate use of Hungarian notation, Indentation and comments. Use of open source software is

encouraged.

In addition to these, instructor may assign one real life application in the form of a mini-project based

on the concepts learned. Instructor may also set one assignment or mini-project that is suitable to

respective branch beyond the scope of syllabus.

Operating System recommended : 64-bit Open source Linux or its derivative

Programming tools recommended: Open Source C Programming tool like GCC

Suggested List of Laboratory Assignments

1. Study of Software Development Life Cycle

2. Study of Unified Modeling language and IBM Rational Rose.




3. Design of Information Flow diagram for Hospital Management System.

4. Design of Use Case diagram for Hospital Management System.

5. Design of Activity diagram for Hospital Management System.

6. Design of Sequence diagram for Hospital Management System.

7. Design of Class diagram for Hospital Management System.

8. Design of State Chart diagram for Hospital Management System.

9. Design of a Mini Project using UML.





Course:Digital ForensicsLab Course Code: YCF712

Teaching

Scheme

(Hrs. /Week)


Examination Total


-- -- 4 2 -- -- -- -- 25 -- 25 50


Prerequisites:

Cyber forensics

Objectives:


1 Demonstrate knowledge and comprehension ofbasic tools and techniques used in the field

of computer forensics sciences.

2 Demonstrate general knowledge and comprehension of digital forensic sciences as a

profession.






neatness.








encouraged.







Group A (Compulsory Assignments)

1. Implementation of following spoofing assignments using C++ multicore Programming

a) IP Spoofing




b) Web Spoofing

2. Write a computer forensic application program in Java/Python/C++ for Recovering Deleted Files

and Deleted Partitions.

3. Write a program in C++ /Python to analyze Email Header.

Group B (Any 7)

1. Develop a GUI and write a Java/Python/C++ program to monitor Network Forensics,

Investigating Logs and Investigating Network Traffic.

2. Write a program in Python for Investigating Wireless Attacks using Multicore

3. Programming

4. Create a Scenario and write a program for overcoming a Website hacking problems and

identifying hacker machine using Java/Python/C++. Develop a prototype website using Ruby on

rails.

5. Write a program in C++ for Tracking Emails and Investigating Email Crimes

6. Install and use Android Mobile Forensics Open Source Tools

7. Install and use an open source tool to Identifying MMS attacks, create necessary Scenario

8. Write a program to identifying private data acquisition of digital evidence using Java in a WiFi

system, use SAN storage(BIGDATA)

9. Write a program to Implement a fingerprint recognition using Java Programming

10. Write a program for identifying the image tampering, voice data

(recorded/Blogged/twitted/Social Web Sites) tampering Python Programming. use SAN

storage(BIGDATA)

11. Write a program for Identifying the tampering of digital signature using Python

12. Write a C++/Java program for Log Capturing and Event Correlation

Group C (Any 1)

1. Implementation of Steganography program

2. Implement a program to generate and verify CAPTCHA image

3. Intrusion Detection System

4. Write a program to detect and prevent windows 8 registry Hacks and Tricks





Course: Dissertation Stage I Course Code: YCF713

Teaching

Scheme

(Hrs. /Week)


Examination Total


-- -- 8 4 -- -- -- -- 50 -- 50 100


Objectives:


1 To develop problem solving abilities using mathematics;

2 To apply algorithmic strategies while solving problems;

3 To develop time and space efficient algorithms;

4 To develop software engineering documents and testing plans;

5 To use algorithmic solutions using distributed, Embedded, concurrent and parallel environments.

Unit

No Details Hours

1

Course (catalog) description: As a part of the B. Tech Curriculum, Dissertation

Stage- I is a Practical course, in which the students of CSE are trained for

project based learning.

Proposed Criteria for Dissertation Evaluation

I suggest the following 9 aspects of every project and presentation. Every item is

worth 10 points out of total 90.

For each of the items I give several key words explaining my understanding of the

item. This grading scheme is only a proposal and is open for any input, discussion

and final approval by members of the seminar. As the evaluation procedure I

suggest for each project and each of the first 8 items to assign a base group to

evaluate it.

Content: (1) Topic: Is the topic chosen interesting, useful, worth researching?

(2) Thesis: Are the theses of the project identifiable, plausible, insightful, and

clear?

(3) Evidence / Sources: Are the sources of information used primary, sufficient,

and relevant? Is evidence clearly related to claims?

(4) Analysis / Logic / Argumentation: Is analysis fresh, posing new ways to think

of the material? Are Ideas represented logically? Is the argument identifiable,

reasonable, and sound? Do authors anticipate and defuse counter-argument?

Presentation: (5) Structure: Is the structure evident, understandable, and appropriate? Is




transition from point to point smooth?

(6) Slides / transparencies: Are slides well designed (not too busy, right font)?

Are graphic and visual appropriate? Any spelling, grammar, word use slips?

(7) Timing: Is presentation timed properly, rehearsed?

(8) Style: Is the level of treatment appropriate (not too detailed or too general)?

Is the presentation energetic, enthusiastic, and clear? Is the volume good?

(9) Extra points for excellence

Tools Required: Preferably 64-bit FOSS tools but if sponsoring company’s requirement is non-open

sourceplatform then it must be latest and current version of non-absolute tools. 64-

bit i5/i7Desktops/Mobiles, Latest SAN,3-tier architectures along with latest

version of FOSS Operating systems like Fedora 21or equivalent, LAMP tools,

WEB server, Applications servers, Database servers, MongoDBor latest open

source BigDATA tools, FOSS Programming Tools like gcc,g++,Eclipse,Python,

Java and other tools are as per the requirement of the SRS. The

documentationtools like Open office, GIT, Latex, Latex-Presentation

Outcomes:


1 An ability to work in actual working environment.

2 An ability to utilize technical resources.

3 An ability to write technical documents and give oral presentations related to the work

completed.





Course: Industry Internship Course Code: YCF714

Teaching

Scheme

(Hrs. /Week)


Examination Total


-- 2 -- 2 -- -- -- -- 50 -- -- 50


Objectives:


1 To expose students to the 'real' working environment and get acquainted with the

organization structure, business operations and administrative functions.

2 To set the stage for future recruitment by potential employers.

Unit

No Details Hours

1

Course (catalog) description: As a part of the B. Tech Curriculum, Industry

Internship is a Practical course, in which the students of CSE are trained for

technical skills.

Grading:

The Course is graded based on:

Presentation : 50%

Student’s reports : 50%

Employers Expectations: Source of highly motivated pre professionals.

Students bring new perspectives to old problems.

Visibility of your organization is increased on campus.

Quality candidates for temporary or seasonal positions and projects.

Freedom for professional staff to pursue more creative projects.

Flexible, cost effective work force not requiring a long term employer

commitment.

Proven, cost effective way to recruit and evaluate potential employees.

Your image in the community is enhanced as you contribute your expertise to the

educational enterprise

Outcomes:





completed.




STUDENT EVALUATION OF INDUSTRY INTERNSHIP

Please respond to the following questions regarding your internship experience.

The purpose of this form is to provide opportunity for an honest appraisal of the internship site and

supervisor.

Organization: ___________________________________________

Semester/Year:_____________

Location: ___________________________________

Supervisor: _________________________________

1. Please rate the following aspects of your internship placement on the basis of this scale:

(0) No Observation, (1) Poor, (2) Fair, (3) Good, (4) Excellent

• Work experience relates to my career goals

• Adequacy of employer supervision

• Helpfulness of supervisor

• Acceptance by fellow workers

• Opportunity to use my training

• Opportunity to develop my human relations skills

• Provided levels of responsibility consistent with my ability and growth

• Opportunity to develop my communication skills

• Opportunity to develop my creativity

• Cooperativeness of fellow workers

• Opportunity to problem solve

• Opportunity to develop critical thinking skills

• Provided orientation to the organization

• Attempt to offer feedback on my progress and abilities

• Effort to make it a learning experience for me

Feel free to explain any of your responses to the above criteria here (use other side if

necessary):

2. Would you work for this supervisor again? ___ Yes ___ No ___ Uncertain

3. Would you work for this organization again? ___ Yes ___ No

Uncertain

4. Would you recommend this organization to other students? ___ Yes ___ No ___ Uncertain

Why or why not?

5. Your Name: _________________________________________ Date: ______________




B. Tech CSE (with Specializationin Cyber Security and Forensics)

Semester – VIII

CIA: Continuous Internal Assessment

L: Theory Lecture

T: Tutorial

P: Practical

TH: Theory Exam.

#: Internship for 15 days.

*: Oral Examination

UC: University Core

PC: Programme Core

PE: Programme Elective

CIA Weightage Description

CIA 1 10% Home Assignment

CIA 2 20% Mid-Term Exam (MTE)

CIA 3 10% Seminar Presentation

CIA 4 10% Research Based Activity

TOTAL 50%

Sr.

No. Core

Course

Code Course Name

Teaching Scheme

(Hrs./Week)

Examination Scheme

Total Marks

L T P C

Formative

Assessment

CIA

Summative

Assessment

ESE

Course Lab Course Lab

1 PC YCF801 Software Testing Methodology 3 1 0 4 50 0 50 0 100

2 PC YCF802 Information Security Intelligence

and Compliance Analytics 3 0 0 3 50 0 50 0 100

3 PE YCFE__ Program Elective 3 0 0 3 50 0 50 0 100

4 PC YCF811 Information Security Intelligence

and Compliance Analytics Lab 0 0 4 2 -- 25 -- 25 50

5 UC YCF812 Dissertation Stage II 0 0 12 8 -- 50 -- 100 150

TOTAL 09 01 16 20 150 75 150 125 500

Program Elective : 1. Advance Software Engineering(YCFE01)

2. Software Project Management(YCFE02)

3. Grid and Cluster Computing(YCFE03)

4. Machine Learning(YCFE04)




Year: Fourth Year Semester – VIII

Course: Software Testing Methodology Course Code: YCF801

Teaching

Scheme

(Hrs. /Week)


Examination Total


3 1 - 4 10 20 10 10 -- 50 -- 100


Prerequisites:


Objectives:


1 To understand the software testing methodologies such as flow graphs and path testing,

transaction flows testing, data flow testing, domain testing and logic base testing.

Unit

No Details Hours

1

Module 1: What is testing?, Purpose of testing, Dichotomies, model for testing,

consequences of bugs, taxonomy of bugs. 4

Module 2:Flow graphs and Path testing:- Basics concepts of path testing,

predicates, path predicates and achievable paths, path sensitising, path

instrumentation, application of path testing.

4

2

Module 1: transaction flows, transaction flow testing techniques. 4

Module 2:Basics of dataflow testing, strategies in dataflow testing, application of

dataflow testing. 3

3

Module 1: domains and paths, Nice & ugly domains, domain testing 4

Module 2:domains and interfaces testing, domain and interface testing, domains

and test ability. 4

4

Module 1:path products & path expression, reduction procedure, applications,

regular expressions & flow anomaly detection. 4

Module 2:Logic Based Testing:- overview, decision tables, path expressions, kv

charts, specifications. 3

5

Module 1:state graphs, good & bad state graphs, state testing, Testability tips. 4

Module 2:Graph Matrices and Application:-Motivational overview, matrix of

graph, relations, power of a matrix, node reduction algorithm, building tools. 4

Outcomes:

1 Ability to apply the process of testing and various methodologies in treating for testing for

developed software.

2 Ability to write test cases for given software to test it before delivery to the customer




Text Books

1. Software Testing techniques — Boris Beizer, Dreamtech, second edition.

2. Software Testing Tools — Dr.K.V.K.K.Prasad, Dreamtech.

Reference Book

1. The craft of software testing – Brian Marick, Pearson Education.

2. Software Testing,3rdedition,P.C. Jorgen sen, Aurbach publications (Dist.by SPD).

3. Software Testing, N.Chauhan, Oxford University press.

4. Introduction to Software Testing, P.Amman n & J offutt, cambridge Univ.Press.

5. Effective methods of Software Testing, perry, John Wiley, 2nd Edition, 1999.

6. Software Testing Concepts and Tools, P.Nageswararaodreamtech Press.





Course: Information Security intelligence and compliance analytics Course Code: YCF802

Teaching

Scheme

(Hrs. /Week)


Examination Total


3 -- -- 3 10 20 10 10 -- 50 -- 100


Prerequisites:

IT Data Security

Objectives:


1 Different security issues in information

2 Concepts of Information Security intelligence

3 Know different tools used for compliance analytics

Unit

No Details Hours

1

Module 1: what is big data?, The arrival of analytics, where is the value?, more to

big data than meets the eye, dealing with the nuances of big data, an open source

brings forth tools, caution: obstacles ahead.

4

Module 2:why big data matters - big data reaches deep, obstacles remain,

Data continue to evolve, data and data analysis are getting more complex, the

future is now, big data and the business case - realizing value, the case for big data,

the rise of big data options, beyond hadoop, with choice come decisions

4

2

Module 1:The data scientist, the team challenge, different teams, different goals. 4

Module 2:don’t forget the data, challenges remain, teams versus culture, gauging

success. 3

3

Module 1:hunting for data, setting the goal, big data sources growing, diving

deeper into big data sources, a wealth of public information, getting started with

big data acquisition, ongoing growth, no end in sight. The storage dilemma,

building a platform, bringing

Structure to unstructured data processing power, choosing among in-house,

Outsourced, or hybrid approaches

4

Module 2:the storage dilemma, building a platform, bringing structure to

unstructured data processing power, choosing among in-house, outsourced, or

hybrid approaches.

4

4

Module 1:pragmatic steps to securing big data, classifying data, protecting big

data analytics 4

Module 2:Big data and compliance, the intellectual property challenge

Big data: the modern era, today, tomorrow, and the next day, changing algorithms. 3




5

Module 1:start small with big data, thinking big, avoiding worst practices, baby

steps, the value of anomalies, expediency versus accuracy, in-memory processing. 4

Module 2:the path to big data, the realities of thinking big data, hands-on big data,

the big data pipeline in depth, big data visualization, big data privacy. 4

Outcomes:


1 Knows Information security fundamentals

2 Tools and techniques used for Security intelligence

Tools and techniques used for compliance analytics

Text Books

Information Security intelligence and compliance analytics (IBM ICE Publication)

Reference Book





Course: Advance Software Engineering Course Code: YCFE01

Teaching

Scheme

(Hrs. /Week)


Examination Total


3 - - 3 10 20 10 10 -- 50 -- 100


Prerequisites:


Objectives:


1 appreciate the wider engineering issues which form the background to developing complex,

evolving (software-intensive) systems

2 plan a software engineering process to account for quality issues and non-functional

requirements

3 employ a selection of concepts and techniques to complete a small-scale study into one of

the advanced topic areas

4 Embark on more in-depth research or practice in software engineering.

Unit

No Details Hours

1 Module 1: Introduction to software engineering. 4

Module 2: , Basics of software engineering. 4

2

Module 1: Embedded software and systems engineering: overview, examples and

industrial realities. 4

Module 2:Project Management - Project Planning and Scheduling

standards,Scheduling. 3

3

Module 1: Unified Software Development Process, Software Process

Improvement, Software Economics, Software Quality. 4

Module 2:Software Metrics - Measurement, Estimation and Prediction,

Requirements Management, Configuration Management, Risk Management,

Testing and Inspection.

4

4

Module 1: Architecture Description Languages, Pattern-Oriented Software

Architecture, Component-based Development. 4

Module 2:Distributed Software Architectures using Middleware, Enterprise

Application Integration, Architectures for Mobile and Pervasive Systems, Model

Driven Architecture.

3

5 Module 1: UML Extension Mechanisms. 4

Module 2:Object Constraint Language, Model Checking. 4




Outcomes:


1 Apply software engineering life cycle by demonstrating competence in communication,

planning, analysis, design, construction, and deployment.

2 Have brief account of associated professional and legal issues.

3 Ability to perform independent research and analysis.

4 Ability to work as an effective member or leader of software engineering teams.

5 To manage time, processes and resources effectively by prioritising competing demands to

achieve personal and team goals Identify and analyzes the common threats in each domain.

Text Books

1. Software Engineering: A Practitioner’s Approach, Roger S Pressman 6th Edition

Reference Book

1. Software Engineering: IyanSomarville, 7th Edition





Course: Software Project Management Course Code: YCFE02

Teaching

Scheme

(Hrs. /Week)


Examination Total


3 - - 3 10 20 10 10 50 100


Prerequisites:

Understanding of software Engineering Process.

Objectives:


1 Explore software project management activities from product concept through

Developmentbased upon case studies and best practices.

Unit

No Details Hours

1

Module 1: Importance of Software Project Management – Activities

Methodologies – Categorization of Software Projects – Setting objectives –

Management Principles – Management Control .

4

Module 2:Project portfolio Management – Cost-benefit evaluation technology –

Risk evaluation – Strategic program Management – Stepwise Project Planning 4

2

Module 1: Software process and Process Models – Choice of Process models –

mental delivery – Rapid Application development – Agile methods – Extreme

Programming .SCRUM – Managing interactive processes – Basics of Software

estimation – Effort and Cost estimation techniques – COSMIC Full function points

– COCOMO II A Parametric Productivity Model – Staffing Pattern.

4

Module 2:SCRUM – Managing interactive processes – Basics of Software

estimation – Effort and Cost estimation techniques – COSMIC Full function points

– COCOMO II A Parametric Productivity Model – Staffing Pattern.

3

3

Module 1: Objectives of Activity planning – Project schedules – Activities –

Sequencing and scheduling – Network Planning models – Forward Pass &

Backward Pass techniques – Critical path (CRM) method.

4

Module 2:Risk identification – Assessment – Monitoring – PERT technique –

Monte Carlo simulation – Resource Allocation – Creation of critical patterns –

Cost schedules.

4

4

Module 1:Framework for Management and control – Collection of data Project

termination – Visualizing progress – Cost monitoring. 4

Module 2:Earned Value Analysis- Project tracking – Change control- Software

Configuration Management – Managing contracts – Contract Management. 3

5 Module 1:Managing people – Organizational behavior – Best methods of staff

selection – Motivation – The Oldham-Hackman job characteristic model – Ethical 4




and Programmed concerns.

Module 2:Working in teams – Decision making – Team structures – Virtual teams

– Communications genres – Communication plans. 4

Outcomes:

At the end of Course students will be able to-

1 To understand Software Project Models and Software Management Concepts

2 To understand the various methods of Cost Estimation

3 To Study about Software Quality Management

4 To Study about Software Metrics.

5 To understand Project Evaluation.

Text Books

1. Bob Hughes, Mike Cotterell and Rajib Mall: Software Project Management – Fifth Edition, Tata

McGraw Hill, New Delhi, 2012.

Reference Book

1. Robert K. Wysocki “Effective Software Project Management” – Wiley Publication,2011.





Course: Grid and Cluster Computing Course Code: YCFE03

Teaching

Scheme

(Hrs. /Week)


Examination Total


3 - - 3 10 20 10 10 -- 50 -- 100


Prerequisites:

Computer Architecture and Programming Concepts, Operating Systems, Data Communication And

Computer Networks

Objectives:


1 To investigate cluster and grid as computing platform for distributed computing.

2 To make students aware of distinguishing characteristics of cluster and grid computing.

3 Introducing software tools used in both cluster and grid computing.

Unit

No Details Hours

1

Module 1: Basic concepts in Distributed Systems, Notion of time 4

Module 2: Introduction to Cluster Computing, Scalable Parallel Computer

Architectures, Cluster Computer and its Architecture, Categories of clusters,

Cluster Components, Cluster Middleware and Single System Image.

4

2

Module 1: Programming Environments and Tools, Networking Protocols and I/O

for clusters, Load Sharing, Load Balancing, Resource Management System,

Process Scheduling, Performance measures and metrics, Detecting and Masking

Faults, Recovering from Faults

4

Module 2:Case Study : Beowulf and PARAM. 3

3

Module 1: Introduction to Message Passing Interface (MPI), Programming using

message-passing - send and receive operations, Message passing interface,

Introduction to MPI routines — send, receive, broadcast, gather, scatter, barrier,

reduction, prefix, all-to-all communication. Demonstration of programs using MPI

routines — matrix-matrix multiplication, quick sort, etc.

4

Module 2:Introducing OpenMP programming. 4

4

Module 1:Introduction to Grid Computing, Difference between Cluster and Grid

computing, Grid Architecture and its key components, Computational, Data,

Enterprise, and, Desktop grids

4

Module 2:Overview of applications of Grid Computing, Grid Infrastructure. 3

5

Module 1:Web Services and Service Oriented Architecture (SAO), Open Grid

Services Architecture (OGSA), OGSA Platform Components, Open Grid Services

Infrastructure (OGSI), OGSA Basic Services, Web Services Resource Framework

(WSRF)

4




Module 2:List of Globally available Middleware, Introducing Grid Computing

Toolkit : Globus, Introducing India’s Grid Computing initiative GARUDA 4

Outcomes: On completion of the course, student will –

1 Be acquainted with various tools and techniques used in the arena of Cluster and Grid

Computing.

2 Able to justify the choice or selection of distributed computing platform for a specific

application.

3 Able to design programs in OpenMP and MPI.

Text Books

1. Prabhu, C. S. R. Grid and cluster computing. PHI Learning Pvt. Ltd., 2008.

2. Quinn, Michael J. Parallel Programming. TMH CSE 526, 2003.

3. Foster, Ian, and Carl Kesselman, eds. The Grid 2: Blueprint for a new computing infrastructure.

Elsevier, 2003.

4. Joseph, Joshy, and Craig Fellenstein. Grid computing. Prentice Hall Professional, 2004.

Reference Book

1. Pacheco, Peter S. Parallel programming with MPI. Morgan Kaufmann, 1997.

2. Buyya, Rajkumar. High performance cluster computing: Architectures and systems (volume 1).

Prentice Hall, Upper SaddleRiver, NJ, USA 1, 999, 1999.





Course: Machine Learning Course Code: YCFE04

Teaching

Scheme

(Hrs. /Week)


Examination Total


3 - - 3 10 20 10 10 -- 50 -- 100


Prerequisites:

Artificial Intelligence, Fuzzy Logic

Objectives:


1 Introduce the fundamental problems of machine learning.

2 Provide understanding of techniques, mathematical concepts, and algorithms used in

machine learning to facilitate further study in this area.

3 Provide pointers into the literature and exercise a project based on literature search and one

or more research papers.

Unit

No Details Hours

1

Module 1: Basic Maths: Probability, Linear Algebra, Convex Optimization 4

Module 2:Background: Statistical Decision Theory, Bayesian Learning (ML,

MAP, Bayes estimates, Conjugate priors) 4

2

Module 1: Regression : Linear Regression, Ridge Regression, Lasso 4

Module 2:Dimensionality Reduction : Principal Component Analysis, Partial

Least Squares 3

3

Module 1: Classification : Linear Classification, Logistic Regression, Linear

Discriminant Analysis, Quadratic Discriminant Analysis, Perceptron, Support

Vector Machines Kernels,

4

Module 2:. Artificial Neural Networks Back Propagation, Decision Trees, Bayes

Optimal Classifier, Naive Bayes. 4

4

Module 1:Evaluation measures : Hypothesis testing, Ensemble Methods,

Bagging Adaboost Gradient Boosting, 4

Module 2:Clustering, K-means, K-medoids, Density-based Hierarchical, Spectral 3

5

Module 1:Miscellaneous topics: Expectation Maximization, GMMs, Learning

theory Intro to Reinforcement Learning 4

Module 2:Graphical Models: Bayesian Networks. 4

Outcomes: On completion of the course, student will –

1 Provide understanding of the limitations of various machine learning algorithms and the




way to evaluate performance of machine learning algorithms.

Text Books

1. Christopher M. Bishop. Pattern Recognition and Machine Learning (Springer)

2. David Barber, Bayesian Reasoning and Machine Learning (Cambridge University Press).

Online version available

3. Tom Mitchell. Machine Learning (McGraw Hill)

4. Richard O. Duda, Peter E. Hart, David G. Stork. Pattern Classification (John Wiley & Sons)

Reference Book

1. T. Hastie, R. Tibshirani, J. Friedman. The Elements of Statistical Learning, 2e, 2008.

2. Christopher Bishop. Pattern Recognition and Machine Learning. 2e




Year: Fourth Year Semester –VIII

Course: Information Security intelligence and compliance

analytics Lab Course Code: YCF811

Teaching

Scheme

(Hrs. /Week)


Examination Total


0 0 4 2 -- -- -- -- 25 0 25 50


Prerequisites:

IT Data Security

Objectives:


1 Different security issues in information

2 Concepts of Information Security intelligence

3 Know different tools used for compliance analytics






neatness.








encouraged.







1. Writing basic program using python

2. Creating program using conditional statements and loops

3. Creating functions in python




4. Creating recursive functions

5. Creating lists, dictionaries in python

6. File handling using python

7. Word count function in python

8. Installing Hadoop

9. Configuring Hadoop

10. Running jobs on Hadoop

11. Working on HDFS

12. Hadoop streaming

13. Creating Mapper function using python.

14. Creating Reducer function using python

15. Python iterator and generators





Course: Dissertation Stage II Course Code: YCF812

Teaching

Scheme (Hrs.

/Week)


Examination Total


-- -- 12 8 -- -- -- -- 50 -- 100 150


Objectives:


1 To expose students to the 'real' working environment and get acquainted with the

organization structure, business operations and administrative functions.

2 To set the stage for future recruitment by potential employers.

3 To develop time and space efficient algorithms;

4 To develop software engineering documents and testing plans;

5 To use algorithmic solutions using distributed, Embedded, concurrent and parallel environments.

Unit

No Details Hours

1

Course (catalog) description: As a part of the B. Tech Curriculum, Dissertation

Stage- II is a Practical course, in which the students of CSE are trained for

project based learning.

Proposed Criteria for Dissertation Evaluation

I suggest the following 9 aspects of every project and presentation. Every item is

worth 10 points out of total 90.

For each of the items I give several key words explaining my understanding of the

item. This grading scheme is only a proposal and is open for any input, discussion

and final approval by members of the seminar. As the evaluation procedure I

suggest for each project and each of the first 8 items to assign a base group to

evaluate it.

Content: (1) Topic: Is the topic chosen interesting, useful, worth researching?

(2) Thesis: Are the theses of the project identifiable, plausible, insightful, and

clear?

(3) Evidence / Sources: Are the sources of information used primary, sufficient,

and relevant? Is evidence clearly related to claims?

(4) Analysis / Logic / Argumentation: Is analysis fresh, posing new ways to think

of the material? Are Ideas represented logically? Is the argument identifiable,

reasonable, and sound? Do authors anticipate and defuse counter-argument?

Presentation:




(5) Structure: Is the structure evident, understandable, and appropriate? Is

transition from point to point smooth?

(6) Slides / transparencies: Are slides well designed (not too busy, right font)?

Are graphic and visual appropriate? Any spelling, grammar, word use slips?

(7) Timing: Is presentation timed properly, rehearsed?

(8) Style: Is the level of treatment appropriate (not too detailed or too general)?

Is the presentation energetic, enthusiastic, and clear? Is the volume good?

(9) Extra points for excellence

Tools Required: Preferably 64-bit FOSS tools but if sponsoring company’s requirement is non-open

sourceplatform then it must be latest and current version of non-absolute tools. 64-

bit i5/i7Desktops/Mobiles, Latest SAN,3-tier architectures along with latest

version of FOSS Operating systems like Fedora 21or equivalent, LAMP tools,

WEB server, Applications servers, Database servers, MongoDBor latest open

source BigDATA tools, FOSS Programming Tools like gcc,g++,Eclipse,Python,

Java and other tools are as per the requirement of the SRS. The

documentationtools like Open office, GIT, Latex, Latex-Presentation

Outcomes:





completed.

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