JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERSITY HYDERABAD

Course Objectives:

• To understand about the intruders.
• To know the intrusion detection and prevention policies

UNIT - I

Introduction: Understanding Intrusion Detection – Intrusion detection and prevention basics – IDS and IPS analysis schemes, Attacks, Detection approaches –Misuse detection – anamoly detection – specification-based detection – hybrid detection THEORETICAL FOUNDATIONS OF DETECTION: Taxonomy of anomaly detection system – fuzzy logic – Bayes theory – Artificial Neural networks – Support vector machine – Evolutionary computation – Association rules – Clustering

UNIT - II

Architecture and Implementation: Centralized – Distributed – Cooperative Intrusion Detection - Tiered architecture

UNIT - III

Justifying Intrusion Detection: Intrusion detection in security – Threat Briefing – Quantifying risk – Return on Investment (ROI)

UNIT - IV

Applications and Tools: Tool Selection and Acquisition Process - Bro Intrusion Detection – Prelude Intrusion Detection - Cisco Security IDS - Snorts Intrusion Detection – NFR security

UNIT - V

Legal Issues and Organizations Standards: Law Enforcement / Criminal Prosecutions – Standard of Due Care – Evidentiary Issues, Organizations and Standardizations.

References:

• 1. Ali A. Ghorbani, Wei Lu, “Network Intrusion Detection and Prevention: Concepts and Techniques”, Springer, 2010.
• 2. Carl Enrolf, Eugene Schultz, Jim Mellander, “Intrusion detection and Prevention”, McGraw Hill, 2004
• 3. Paul E. Proctor, “The Practical Intrusion Detection Handbook “, Prentice Hall, 2001.
• 4. Ankit Fadia and Mnu Zacharia, “Intrusiion Alert”, Vikas Publishing house Pvt., Ltd, 2007.
• 5. Earl Carter, Jonathan Hogue, “Intrusion Prevention Fundamentals”, Pearson Education, 2006. R19 M. TECH. CN/CNIS/CYBER SECURITY M. Tech. (CNIS/CN/Cyber Security) – I Year – II Semester Common to CNIS, CN and Cyber Security