Intrusion Detection And Prevention Systems

Catalog description

This course will cover the fundamental concepts and design implications required to develop and implement intrusion detection and prevention systems that address security violations in computer systems. Topics to be covered include: main classes of attacks against computer systems, taxonomy and architecture of intrusion detection and prevention systems, network traffic analysis and feature extraction algorithms, signature and anomaly based techniques, key heuristic based and machine learning based techniques and algorithms for intrusion detection. Intrusion detection and prevention systems performance evaluation and issues related to security and defense in depth will also be addressed. Typically offered Fall Spring Summer. Course Learning Outcomes 1. Understand and implement classes of attack to computer systems. 2. Have a good grasp of the design and implementation of signature based and anomaly based techniques to solve problems related to intrusion detection and prevention. 3. Employ ID&PS specific feature extraction techniques and machine learning skills to applied industry or research problems. 4. Collaborate with team members to deliver a solution with limited resources and time. 5. Conduct independent research under the instructor’s guidance. 6. Conduct intrusion detection and prevention related research that meets peer reviewed publication standards. View Class Schedule