CEC Faculty Proceedings, Presentations, Speeches and Lectures


Next Generation Intrusion Detection: Autonomous Reinforcement Learning of Network Attacks

Event Location / Date(s)

Baltimore, MD / 2000

Document Type

Conference Proceeding

Presentation Date


Conference Name / Publication Title

Proceedings of the 23rd National Information Systems Security Conference


The timely and accurate detection of computer and network system intrusions has always been an elusive goal for system administrators and information security researchers. Existing intrusion detection approaches require either manual coding of new attacks in expert systems or the complete retraining of a neural network to improve analysis or learn new attacks. This paper presents a new approach to applying adaptive neural networks to intrusion detection that is capable of autonomously learning new attacks rapidly through the use of a modified reinforcement learning method that uses feedback from the protected system. The approach has been demonstrated to be extremely effective in learning new attacks, detecting previously learned attacks in a network data stream, and in autonomously improving its analysis over time using feedback from the protected system.

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