Title

Adaptive Critic Design for Computer Intrusion Detection System

Abstract

This paper summarizes ongoing research. A neural network is used to detect a computer system intrusion basing on data from the system audit trail generated by Solaris Basic Security Module. The data have been provided by Lincoln Labs, MIT. The system alerts the human operator, when it encounters suspicious activity logged in the audit trail. To reduce the false alarm rate and accommodate the temporal indefiniteness of moment of attack a reinforcement learning approach is chosen to train the network.

Department(s)

Electrical and Computer Engineering

Second Department

Engineering Management and Systems Engineering

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2001 SPIE -- The International Society for Optical Engineering, All rights reserved.


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