Anna University Semester 7 Information Technology Engineering Syllabus – The Anna University Seventh semester syllabus for Information Technology engineering in Bachelors degree B.E or B.Tech has four main subjects and one elective.The most important subjects of this semester are Grid Cloud computing,Network Security and Data Mining.All these subjects are relevant from a career perspective.
UNIT I DATABASE MODELLING, MANAGEMENT AND DEVELOPMENT 9
Database design and modelling – Business Rules and Relationship; Java database Connectivity
(JDBC), Database connection Manager, Stored Procedures. Trends in Big Data systems including
NoSQL – Hadoop HDFS, MapReduce, Hive, and enhancements.
UNIT II DATA SECURITY AND PRIVACY 9
Program Security, Malicious code and controls against threats; OS level protection; Security –
Firewalls, Network Security Intrusion detection systems. Data Privacy principles. Data Privacy Laws
UNIT III INFORMATION GOVERNANCE 9
Master Data Management (MDM) – Overview, Need for MDM, Privacy, regulatory requirements and
compliance. Data Governance – Synchronization and data quality management.
UNIT IV INFORMATION ARCHITECTURE 9
Principles of Information architecture and framework, Organizing information, Navigation systems and
Labelling systems, Conceptual design, Granularity of Content.
UNIT V INFORMATION LIFECYCLE MANAGEMENT 9
Data retention policies; Confidential and Sensitive data handling, lifecycle management costs. Archive
data using Hadoop; Testing and delivering big data applications for performance and functionality;
Challenges with data administration;
CRYPTOGRAPHY AND NETWORK SECURITY
UNIT I INTRODUCTION & NUMBER THEORY 10
Services, Mechanisms and attacks-the OSI security architecture-Network security model-Classical
Encryption techniques (Symmetric cipher model, substitution techniques, transposition techniques,
steganography).FINITE FIELDS AND NUMBER THEORY: Groups, Rings, Fields-Modular arithmeticEuclid?s
algorithm-Finite fields- Polynomial Arithmetic –Prime numbers-Fermat?s and Euler?s theoremTesting
for primality -The Chinese remainder theorem- Discrete logarithms.
UNIT II BLOCK CIPHERS & PUBLIC KEY CRYPTOGRAPHY 10
Data Encryption Standard-Block cipher principles-block cipher modes of operation-Advanced
Encryption Standard (AES)-Triple DES-Blowfish-RC5 algorithm. Public key cryptography: Principles
of public key cryptosystems-The RSA algorithm-Key management – Diffie Hellman Key exchangeElliptic
curve arithmetic-Elliptic curve cryptography.
UNIT III HASH FUNCTIONS AND DIGITAL SIGNATURES 8
Authentication requirement – Authentication function – MAC – Hash function – Security of hash
function and MAC –MD5 – SHA – HMAC – CMAC – Digital signature and authentication protocols –
DSS – EI Gamal – Schnorr.
UNIT IV SECURITY PRACTICE & SYSTEM SECURITY 8
Authentication applications – Kerberos – X.509 Authentication services – Internet Firewalls for Trusted
System: Roles of Firewalls – Firewall related terminology- Types of Firewalls – Firewall designs – SET
for E-Commerce Transactions. Intruder – Intrusion detection system – Virus and related threats –
Countermeasures – Firewalls design principles – Trusted systems – Practical implementation of
cryptography and security.
UNIT V E-MAIL, IP & WEB SECURITY 9
E-mail Security: Security Services for E-mail-attacks possible through E-mail – establishing keys
privacy-authentication of the source-Message Integrity-Non-repudiation-Pretty Good Privacy-S/MIME.
IPSecurity: Overview of IPSec – IP and IPv6-Authentication Header-Encapsulation Security Payload
(ESP)-Internet Key Exchange (Phases of IKE, ISAKMP/IKE Encoding). Web Security: SSL/TLS
Basic Protocol-computing the keys- client authentication-PKI as deployed by SSLAttacks fixed in v3-
Exportability-Encoding-Secure Electronic Transaction (SET).
DATA WAREHOUSING AND DATA MINING
UNIT I DATA WAREHOUSING 9
Data warehousing Components –Building a Data warehouse –- Mapping the Data Warehouse to a
Multiprocessor Architecture – DBMS Schemas for Decision Support – Data Extraction, Cleanup, and
Transformation Tools –Metadata.
UNIT II BUSINESS ANALYSIS 9
Reporting and Query tools and Applications – Tool Categories – The Need for Applications – Cognos
Impromptu – Online Analytical Processing (OLAP) – Need – Multidimensional Data Model – OLAP
Guidelines – Multidimensional versus Multirelational OLAP – Categories of Tools – OLAP Tools and
UNIT III DATA MINING 9
Introduction – Data – Types of Data – Data Mining Functionalities – Interestingness of Patterns –
Classification of Data Mining Systems – Data Mining Task Primitives – Integration of a Data Mining
System with a Data Warehouse – Issues –Data Preprocessing.
UNIT IV ASSOCIATION RULE MINING AND CLASSIFICATION 9
Mining Frequent Patterns, Associations and Correlations – Mining Methods – Mining various Kinds of
Association Rules – Correlation Analysis – Constraint Based Association Mining – Classification and
Prediction – Basic Concepts – Decision Tree Induction – Bayesian Classification – Rule Based
Classification – Classification by Back propagation – Support Vector Machines – Associative
Classification – Lazy Learners – Other Classification Methods – Prediction.
UNIT V CLUSTERING AND TRENDS IN DATA MINING 9
Cluster Analysis – Types of Data – Categorization of Major Clustering Methods – K-means–
Partitioning Methods – Hierarchical Methods – Density-Based Methods –Grid Based Methods –
Model-Based Clustering Methods – Clustering High Dimensional Data – Constraint – Based Cluster
Analysis – Outlier Analysis – Data Mining Applications.
GRID AND CLOUD COMPUTING
UNIT I INTRODUCTION 9
Evolution of Distributed computing: Scalable computing over the Internet – Technologies for network
based systems – clusters of cooperative computers – Grid computing Infrastructures – cloud
computing – service oriented architecture – Introduction to Grid Architecture and standards –
Elements of Grid – Overview of Grid Architecture.
UNIT II GRID SERVICES 9
Introduction to Open Grid Services Architecture (OGSA) – Motivation – Functionality Requirements –
Practical & Detailed view of OGSA/OGSI – Data intensive grid service models – OGSA services.
UNIT III VIRTUALIZATION 9
Cloud deployment models: public, private, hybrid, community – Categories of cloud computing:
Everything as a service: Infrastructure, platform, software – Pros and Cons of cloud computing –
Implementation levels of virtualization – virtualization structure – virtualization of CPU, Memory and
I/O devices – virtual clusters and Resource Management – Virtualization for data center automation.
UNIT IV PROGRAMMING MODEL 9
Open source grid middleware packages – Globus Toolkit (GT4) Architecture , Configuration – Usage
of Globus – Main components and Programming model – Introduction to Hadoop Framework –
Mapreduce, Input splitting, map and reduce functions, specifying input and output parameters,
configuring and running a job – Design of Hadoop file system, HDFS concepts, command line and
java interface, dataflow of File read & File write.
UNIT V SECURITY 9
Trust models for Grid security environment – Authentication and Authorization methods – Grid
security infrastructure – Cloud Infrastructure security: network, host and application level – aspects of
data security, provider data and its security, Identity and access management architecture, IAM
practices in the cloud, SaaS, PaaS, IaaS availability in the cloud, Key privacy issues in the cloud.