JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERSITY HYDERABAD

Pre-Requisites:

• A course on “Database Management Systems”
• Knowledge of probability and statistics

Course Objectives:

• It presents methods for mining frequent patterns, associations, and correlations.
• It then describes methods for data classification and prediction, and data–clustering approaches.
• It covers mining various types of data stores such as spatial, textual, multimedia, streams.

Course Outcomes:

• Ability to understand the types of the data to be mined and present a general classification of tasks and primitives to integrate a data mining system.
• Apply preprocessing methods for any given raw data.
• Extract interesting patterns from large amounts of data.
• Discover the role played by data mining in various fields.
• Choose and employ suitable data mining algorithms to build analytical applications
• Evaluate the accuracy of supervised and unsupervised models and algorithms.

UNIT - I

Data Mining: Data–Types of Data–, Data Mining Functionalities– Interestingness Patterns– Classification of Data Mining systems– Data mining Task primitives –Integration of Data mining system with a Data warehouse–Major issues in Data Mining–Data Preprocessing.

UNIT - II

Association Rule Mining: Mining Frequent Patterns–Associations and correlations – Mining Methods– Mining Various kinds of Association Rules– Correlation Analysis– Constraint based Association mining. Graph Pattern Mining, SPM.

UNIT - III

Classification: Classification and Prediction – Basic concepts–Decision tree induction–Bayesian classification, Rule–based classification, Lazy learner.

UNIT - IV

Clustering and Applications: Cluster analysis–Types of Data in Cluster Analysis–Categorization of Major Clustering Methods– Partitioning Methods, Hierarchical Methods– Density–Based Methods, Grid–Based Methods, Outlier Analysis.

UNIT - V

Advanced Concepts: Basic concepts in Mining data streams–Mining Time–series data––Mining sequence patterns in Transactional databases– Mining Object– Spatial– Multimedia–Text and Web data – Spatial Data mining– Multimedia Data mining–Text Mining– Mining the World Wide Web.

TEXT BOOKS:

• 1. Data Mining – Concepts and Techniques – Jiawei Han & Micheline Kamber, 3rd Edition Elsevier.
• 2. Data Mining Introductory and Advanced topics – Margaret H Dunham, PEA.

REFERENCE BOOK:

• 1. Ian H. Witten and Eibe Frank, Data Mining: Practical Machine Learning Tools and Techniques (Second Edition), Morgan Kaufmann, 2005. IT711PE: WEB SECURITY (Professional Elective - IV) IV Year B.Tech. IT I - Sem L T P C 3 0 0 3

Course Objectives:

• Give an Overview of information security
• Give an overview of Access control of relational databases

Course Outcomes

Students should be able to

• Understand the Web architecture and applications
• Understand client side and service side programming
• Understand how common mistakes can be bypassed and exploit the application
• Identify common application vulnerabilities

UNIT - I

The Web Security, The Web Security Problem, Risk Analysis and Best Practices Cryptography and the Web: Cryptography and Web Security, Working Cryptographic Systems and Protocols, Legal Restrictions on Cryptography, Digital Identification

UNIT - II

The Web’s War on Your Privacy, Privacy-Protecting Techniques, Backups and Antitheft, Web Server Security, Physical Security for Servers, Host Security for Servers, Securing Web Applications

UNIT - III

Database Security: Recent Advances in Access Control, Access Control Models for XML, Database Issues in Trust Management and Trust Negotiation, Security in Data Warehouses and OLAP Systems

UNIT - IV

Security Re-engineering for Databases: Concepts and Techniques, Database Watermarking for Copyright Protection, Trustworthy Records Retention, Damage Quarantine and Recovery in Data Processing Systems, Hippocratic Databases: Current Capabilities and

UNIT - V

Future Trends Privacy in Database Publishing: A Bayesian Perspective, Privacy-enhanced Location- based Access Control, Efficiently Enforcing the Security and Privacy Policies in a Mobile Environment

TEXT BOOK:

• 1. Web Security, Privacy and Commerce Simson G Arfinkel, Gene Spafford, O’Reilly.
• 2. Handbook on Database security applications and trends Michael Gertz, Sushil Jajodia