A new approach to characterizing masqueraders is presented, which can be used to optimize intrusion-detection systems. With this approach the masquerader characteristics are derived from a sample of user behavior and a parameter called the masquerading factor. The derivation is based on the simplest case of a game-theoretic formulation of the intrusion-detection problem, where the masquerader emulates the user characteristics as closely as its knowledge about the user behavior permits. The extent of this knowledge is represented by the masquerading factor. A rule-based anomaly-detection system is used to demonstrate the proposed characterization approach. Numerical results show that, even though the masquerading factor is not known, the approach allows comparison of system alternatives.
By: Mehdi Nassehi
Published in: RZ3003 in 1998
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