Probabilistic suffix models for API sequence analysis of windows XP applications

DOI10.1016/j.patcog.2007.04.006zbMath1122.68397OpenAlexW2107313432MaRDI QIDQ2384957

Geoffrey Mazeroff, Richard Ford, Jens Gregor, Michael G. Thomason

Publication date: 10 October 2007

Published in: Pattern Recognition (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.patcog.2007.04.006

zbMATH Keywords

virusanomaly detectionagglomerative clusteringwormAPI sequence classificationmalicious mobile codeProbabilistic suffix modelwindows XP

Mathematics Subject Classification ID

Pattern recognition, speech recognition (68T10) Theory of operating systems (68N25) Theory of software (68N99)

Cites Work

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• The power of amnesia: Learning probabilistic automata with variable memory length
• Computer intrusion: Detecting masquerades.
• Host-based intrusion detection using dynamic and static behavioral models

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