Anzeige
Erschienen in:
2006 | OriginalPaper | Buchkapitel
Behavioral Distance Measurement Using Hidden Markov Models
verfasst von : Debin Gao, Michael K. Reiter, Dawn Song
Erschienen in: Recent Advances in Intrusion Detection
Verlag: Springer Berlin Heidelberg
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
The
behavioral distance
between two processes is a measure of the deviation of their behaviors. Behavioral distance has been proposed for detecting the compromise of a process, by computing its behavioral distance from another process executed on the same input. Provided that the two processes are diverse and so unlikely to fall prey to the same attacks, an increase in behavioral distance might indicate the compromise of one of them. In this paper we propose a new approach to behavioral distance calculation using a new type of Hidden Markov Model. We also empirically evaluate the intrusion detection capability of our proposal when used to measure the distance between the system-call behaviors of diverse web servers. Our experiments show that it detects intrusions with substantially greater accuracy and with performance overhead comparable to that of prior proposals.