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Proceedings Paper

Adaptive critic design for computer intrusion detection system
Author(s): Alexander Novokhodko; Donald C. Wunsch; Cihan H. Dagli
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Paper 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.

Paper Details

Date Published: 21 March 2001
PDF: 7 pages
Proc. SPIE 4390, Applications and Science of Computational Intelligence IV, (21 March 2001); doi: 10.1117/12.421156
Show Author Affiliations
Alexander Novokhodko, Univ. of Missouri/Rolla (United States)
Donald C. Wunsch, Univ. of Missouri/Rolla (United States)
Cihan H. Dagli, Univ. of Missouri/Rolla (United States)


Published in SPIE Proceedings Vol. 4390:
Applications and Science of Computational Intelligence IV
Kevin L. Priddy; Paul E. Keller; Peter J. Angeline, Editor(s)

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