Adaptive critic design for computer intrusion detection system

Alexander Novokhodko; Donald C. Wunsch II; Cihan H. Dagli

doi:10.1117/12.421156

21 March 2001 Adaptive critic design for computer intrusion detection system

Alexander Novokhodko, Donald C. Wunsch II, Cihan H. Dagli

Proceedings Volume 4390, Applications and Science of Computational Intelligence IV; (2001) https://doi.org/10.1117/12.421156
Event: Aerospace/Defense Sensing, Simulation, and Controls, 2001, Orlando, FL, United States

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.

Citation Download Citation

Alexander Novokhodko, Donald C. Wunsch II, and Cihan H. Dagli "Adaptive critic design for computer intrusion detection system", Proc. SPIE 4390, Applications and Science of Computational Intelligence IV, (21 March 2001); https://doi.org/10.1117/12.421156

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