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RAID
2004
Springer

Anomaly Detection Using Layered Networks Based on Eigen Co-occurrence Matrix

10 years 7 months ago
Anomaly Detection Using Layered Networks Based on Eigen Co-occurrence Matrix
Anomaly detection is a promising approach to detecting intruders masquerading as valid users (called masqueraders). It creates a user profile and labels any behavior that deviates from the profile as anomalous. In anomaly detection, a challenging task is modeling a user’s dynamic behavior based on sequential data collected from computer systems. In this paper, we propose a novel method, called Eigen co-occurrence matrix (ECM), that models sequences such as UNIX commands and extracts their principal features. We applied the ECM method to a masquerade detection experiment with data from Schonlau et al. We report the results and compare them with results obtained from several conventional methods.
Mizuki Oka, Yoshihiro Oyama, Hirotake Abe, Kazuhik
Added 02 Jul 2010
Updated 02 Jul 2010
Type Conference
Year 2004
Where RAID
Authors Mizuki Oka, Yoshihiro Oyama, Hirotake Abe, Kazuhiko Kato
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