Information technology engineering semester 6 syllabus

Information technology engineering semester 6 syllabus – The syllabus for sixth semester Information Technology Engineering from Mumbai University degree course in Bachelors of Engineering B.E has the main subjects of Systems and web security, Software engineering, Data Mining Business Intelligence and Distributed Systems. 

 

Information technology engineering semester 6 syllabus

 

SOFTWARE ENGINEERING

Introduction to
Software
Engineering
Professional Software Development, Layered
Technology, Process framework, CMM, Process
Patterns and Assessment
03
2 Process Models Prescriptive Models : Waterfall Model, Incremental,
RAD Models Evolutionary Process Models:Prototyping,
Spiral and Concurrent Development Model Specialized
Models: Component based, Aspect Oriented development
06
03 Agile Software
Development
Agile Process and Process Models, Adaptive and
Dynamic system Development, Scrum, Feature Driven
Development and Agile Modeling
03
04 Engineering and
Modeling
Practices
Core Principles, Communication, Planning, Modeling,
Construction and deployment. System Modeling and
UML
04
05 Requirements
Engineering and
Analysis Model
Requirements Engineering Tasks, Elicitation, building
analysis model, Data Modeling concepts, Object
Oriented Analysis
06
06 Design
Engineering
Design Concepts, Design Model – Data, Architecture,
Interface, Component Level and Deployment Level
design elements
05
07 Testing strategies
and tactics
Testing strategies for conventional and Object Oriented
architectures, Validation and system testing
Software testing fundamentals, Black box and white box
testing, Object Oriented testing methods
06
08 Metrics for
Process and
Projects
Process Metrics and Project Metrics, Software
Measurement, Object Oriented Metrics, Software Project
Estimation, Decomposition Techniques, LOC based, FP
based and Use case based estimations, Empirical
estimation Models
06
University of Mumbai, Information Technology (semester VI) (Rev?2012)
6
09 Risk Management Risk strategies, Software risks, Risk Identification,
Projection, RMMM
03
10 Quality
Management
Quality Concepts, SQA activities, Software reviews,
FTR, Software reliability and measures, SQA plan
03
11 Change
Management
Software Configuration Management, elements of SCM,
SCM Process, Change Control
03
Text Books:
1. “Software Engineering : APractitioner?s Approach” by Roger Pressman Sixth Edition
2. “Software Engineering” by Ian Sommerville, Pearson
3. “Software Engineering : A Precise Approach” Pankaj Jalote , Wiley India
References: (for Practical)
1. “System Analysis and Design” Alan Dennis, Wixom, R M Roth – Wiley India
2. “Software Engineering : Principles and Practice” by Waman S Jawadekar

 

DISTRIBUTED SYSTEMS

Fundamentals Introduction, Distributed Computing Models, Software
Concepts, Issues in designing Distributed System, Client –
Server Model
4
2 Communication Message Passing , Introduction to Message Passing,
Advantages and features of Message Passing, Message
Format, Message Buffering, Multi Data gram Messaging ,
Group Communication
Remote Procedure Call (RPC): Basic RPC Operations,
Parameter Passing, Extended RPC Models
Remote Object Invocation: Distributed Objects, Binding a
Client to an Object, Static Vs Dynamic RMI, Parameter
Passing, Java RMI
Message Oriented Communication: Persistence and
synchronicity in communication, Message Oriented
Transient and Persistent Communications
8
3 Processes Threads, Code Migration: Approaches to Code Migration,
Migration and Local Resources, Migration in
Heterogeneous Systems
4
4 Synchronization Clock Synchronization, Physical and Logical Clocks,
Global State, Election Algorithms, Mutual Exclusion,
Distributed Transactions, Deadlocks
8
5 Consistency and
Replication
Introduction, Data-Centric Consistency Models, Client
Centric Consistency Models, Distributed Protocols
8
6 Distributed
Technologies and
Frameworks
Overview of EJB S/W Architecture, view of EJB
Conversation, Building and Deploying EJB, Roles in EJB,
Types of Enterprise Beans, Lifecycle of Beans ,
Developing Applications using EJB Framework.
5
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10
Introduction to CORBA, CORBA Components and
architecture, Method Invocation, Static and Dynamic
Invocation in CORBA, CORBA IDL, Developing
Application using CORBA
4
Introduction to .NET, .NET architecture, . NET Remoting 3
Comparison of RMI, CORBA, EJB, .NET 1
7. Service Oriented
Architecture
Defining SOA, Business value of SOA, SOA
characteristics, Concept of a service, SOA Architecture,
Deploying SOA applications.
3
Text Books:
? Sunita Mahajan, Seema Shah, “ Distributed Computing”, Oxford, second edition.
? Andrew S. Tanenbaum & Maarten van Steen “ Distributed Systems : Principles
and paradigms” Prentice Hall of India Private Limited
? G. Sudha Sadasivam, Radha Shankarmani, “Middleware and Enterprise Integration
Technologies ” , Wiley Precise Textbook
References:
1. Pradeep K. Sinha “Distributed Operating Systems”, Prentice Hall of India Private
Limited
2. Thomas Erl “Service Oriented Architecture : Concepts, Technology and Design” Prentice
Hall
3. G. Coulouris, J. Dollimore and T. Kindberg “Distributed Systems :

 

SYSTEM AND WEB SECURITY

Introduction to
Computer Security
Vulnerabilities, Threats and Attacks, Public Key
Cryptography and Cryptanalysis, Knapsack
cryptosystem
04
2 Authentication Authentication Methods and Protocols, Password
based authentication, Token Based Authentication,
Biometric Authentication, Digital Certificates, X.
509 Directory Services, PKI, Needham Schroeder
Authentication Protocol, Single sign on, Kerberos
Authentication Protocol, Federated Identity Management.
08
3 Access Control Access control Policies: DAC, MAC, RBAC, Access
control Matrix, ACLs and Capability Lists, Multiple level
security model: Biba and Bell La Padula Models, Multilateral
security, Covert channel, CAPTCHA.
06
4 Software security Software Flaws, Buffer Overflow, Incomplete
Mediation, Race conditions, Malware: Viruses, Worms,
Trojans, Logic Bomb, Bots, Rootkits, Miscellaneous Software
Attacks: Salami attack, Linearization Attacks, Trusted
Computing: Software reverse engineering, Digital Rights
management
08
5 Operating System
Security
Linux Security Model, File System Security, Linux
Vulnerabilities, Windows Security Architecture, Windows
Vulnerabilities
04
6 Network Security Network security basics, TCP/IP vulnerabilities Layer
wise: Packet Sniffing, ARP spoofing, port scanning, IP spoofing,
TCP syn flood, DNS Spoofing, Internet Security Protocols: SSL,
TLS, IPSEC, Secure Email and S/MIME, Denial of Service:
Classic DOS attacks, Source Address spoofing, ICMP flood,
SYN flood, UDP flood, Distributed Denial of Service, Defenses
against Denial of Service Attacks.
Firewalls, Intrusion Detection Systems: Host Based and
Network Based IDS, Honey pots.
12
7 Web Security User Authentication and session management, Cookies,
Secure HTTP, SQL Injection Techniques, Cross Site Scripting,
Cross-Site Request Forgery, Session Hijacking and
Management, Phishing and Pharming Techniques, Web
Services Security.
06
University of Mumbai, Information Technology (semester VI) (Rev?2012)
14
Text Books
1) Computer Security Principles and Practice, by William Stallings, Pearson Education.
2) Security in Computing by Charles P. Pfleeger , Pearson Education
3) Computer Security by Dieter Gollman, 3rd Edition, Wiley India.
4) Cryptography and Network Security by Behrouz A. Forouzan, TATA McGraw hill.
Reference Books
1) Information security Principles and Practice by Mark Stamp, Wiley publication
2) OWASP TOP 10: https://www.owasp.org/index.php/Top_10_2013
3) Network security bible 2nd edition, Eric Cole, Wiley India.

 

Data Mining and Business Intelligence

Introduction to
Data Mining
What is Data Mining; Kind of patterns to be mined;
Technologies used; Major issues in Data Mining
02
2 Data Exploration Types of Attributes; Statistical Description of Data;
Data Visualization; Measuring similarity and
dissimilarity.
04
3 Data
Preprocessing
Why Preprocessing? Data Cleaning; Data Integration;
Data Reduction: Attribute subset selection, Histograms,
Clustering and Sampling; Data Transformation & Data
Discretization: Normalization, Binning, Histogram
Analysis and Concept hierarchy generation.
04
4 Classification Basic Concepts;
Classification methods:
1. Decision Tree Induction: Attribute Selection
Measures, Tree pruning.
2. Bayesian Classification: Naïve Bayes? Classifier.
Prediction: Structure of regression models; Simple
linear regression, Multiple linear regression.
Model Evaluation & Selection: Accuracy and Error
measures, Holdout, Random Sampling, Cross
Validation, Bootstrap; Comparing Classifier
performance using ROC Curves.
Combining Classifiers: Bagging, Boosting, Random
Forests.
08
5 Clustering Cluster Analysis: Basic Concepts;
Partitioning Methods: K-Means, K-Mediods;
Hierarchical Methods: Agglomerative, Divisive,
BIRCH;
Density-Based Methods: DBSCAN, OPTICS
08
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6 Outlier Analysis What are outliers? Types, Challenges;
Outlier Detection Methods: Supervised, SemiSupervised,
Unsupervised, Proximity based, Clustering
Based.
02
7 Frequent Pattern
Mining
Market Basket Analysis, Frequent Itemsets, Closed
Itemsets, and Association Rules;
Frequent Pattern Mining, Efficient and Scalable
Frequent Itemset Mining Methods, The Apriori
Algorithm for finding Frequent Itemsets Using
Candidate Generation, Generating Association Rules
from Frequent Itemsets, Improving the Efficiency of
Apriori,
A pattern growth approach for mining Frequent
Itemsets;
Mining Frequent itemsets using vertical data formats;
Mining closed and maximal patterns;
Introduction to Mining Multilevel Association Rules
and Multidimensional Association Rules; From
Association Mining to Correlation Analysis, Pattern
Evaluation Measures; Introduction to Constraint-Based
Association Mining.
08
8 Business
Intelligence
What is BI? Effective and timely decisions; Data,
information and knowledge; The role of mathematical
models; Business intelligence architectures; Enabling
factors in business intelligence project; Development of
a business intelligence system; Ethics and business
intelligence
03
9 Decision Support
System
Representation of the decision-making process;
Evolution of information systems; Definition of
decision support system; Development of a decision
support system.
03
10 BI Applications Data mining for business Applications like Fraud
Detection, Clickstream Mining, Market Segmentation,
retail industry, telecommunications industry, banking &
finance CRM etc
06
Text Books:
1. Han, Kamber, “Data Mining Concepts and Techniques”, Morgan Kaufmann 3nd Edition
2. G. Shmueli, N.R. Patel, P.C. Bruce, “Data Mining for Business Intelligence: Concepts,
Techniques, and Applications in Microsoft Office Excel with XLMiner”, 1st Edition, Wiley
India.
University of Mumbai, Information Technology (semester VI) (Rev?2012)
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3. Business Intelligence: Data Mining and Optimization for Decision Making by Carlo
Vercellis ,Wiley India Publications
Reference Books:
1. P. N. Tan, M. Steinbach, Vipin Kumar, “Introduction to Data Mining”, Pearson Education
2. Michael Berry and Gordon Linoff “Data Mining Techniques”, 2nd Edition Wiley
Publications.
3. Michael Berry and Gordon Linoff “Mastering Data Mining- Art & science of CRM”, Wiley
Student Edition
4. Vikram Pudi & Radha Krishna, “Data Mining”, Oxford Higher Education.

 

ADVANCED INTERNET TECHNOLOGY

Search Engine
Optimization
Search Engine Basics
Algorithm based Ranking Systems – Determining
Searcher Intent and Delivering Relevant, Fresh Content,
Analyzing Ranking Factors, Using Advanced Search
Techniques, Vertical Search Techniques, CountrySpecific
Search Engines
20
University of Mumbai, Information Technology (semester VI) (Rev?2012)
21
Determining SEO Objective and Finding Your Site?s
Audience – Setting SEO Goals and Objective,
Developing SEO plans Perior to Site Deveopment –
SEO for Rawtraffic;E-commerce
Sales;Mindsahre/Branding; Direct Marketing;
Reputation Management; Ideological Influence
Getting started SEO: Defining Your Site?s Information
Architecture, Auditing an Existing Site to identify SEO
Problems, Identifying Current Server Statistic Software
and Gaining Access – Dtermining Top competitors,
Benchmarking Current Indexing Status, Current
Rankings, Benchmarking Current Traffic Source and
Volumes, Conduct SEO/Website SWOT analysis.
Keyword Genration – Creating Pages – Website
Structure- Creating Content-Creating Communitiesbuilding
Links-Using Google Analytics-Social Media
Optimization-Creating Pay-per-click CampaignsOptimizing
PPC Campaigns through Quality Score
optimization – Tracking Results and Measuring Success.
2. Responsive web
design with
HTML5 and CSS3
Getting Started with HTML 5, CSS3 and Responsive
Web Design.
16
Media Queries: Supporting Differing Viewports
Embracing Fluid Layout
HTML 5 for Responsive Design
CSS3: Selectors, Typography and color Modes
Stunning Aesthetics with CSS3
CSS3 Transitions, Transformations and Animations
Conquer Forms HTML5 and CSS3
University of Mumbai, Information Technology (semester VI) (Rev?2012)
22
3. RIA and Mashup Characteristic of RIA – Web Mashup Eco Systems –
Mashup Techniques :1) Mashing on the Web Server,
Rich User Interface using Ajax, Mashing with JSON
RIA: Ajax vs Traditional Approach
Technical Background:
1) Javascript and AJAX
2) JSON Alternative to XML
3) Syndication
4) REST and WS * Web Services
12
Text Books:
1. Professional Web 2.0 Programming WROX press
2. Responsive Web Design with HTML5 and CSS3 PACKT
3. The Art of SEO O?Reilly Publication
References:
1. Rich Internet Application AJAX and Beyond WROX press
2. Web Technology, Srinivasan, Pearson