Learning classifiers for misuse and anomaly detection using a bag of system calls representation

Dae Ki Kang, Doug Fuller, Vasant Honavar

Research output: Chapter in Book/Report/Conference proceedingConference contribution

74 Citations (Scopus)

Abstract

In this paper, we propose a "bag of system calls" representation for intrusion detection in system call sequences and describe misuse and anomaly detection results with standard machine learning techniques on University of New Mexico (UNM) and MIT Lincoln Lab (MIT LL) system call sequences with the proposed representation. With the feature representation as input, we compare the performance of several machine learning techniques for misuse detection and show experimental results on anomaly detection. The results show that standard machine learning and clustering techniques on simple "bag of system calls" representation of system call sequences is effective and often performs better than those approaches that use foreign contiguous subsequences in detecting intrusive behaviors of compromised processes.

Original languageEnglish (US)
Title of host publicationProceedings from the Sixth Annual IEEE System, Man and Cybernetics Information Assurance Workshop, SMC 2005
Pages118-125
Number of pages8
DOIs
StatePublished - Dec 1 2005
Event6th Annual IEEE System, Man and Cybernetics Information Assurance Workshop, SMC 2005 - West Point, NY, United States
Duration: Jun 15 2005Jun 17 2005

Publication series

NameProceedings from the 6th Annual IEEE System, Man and Cybernetics Information Assurance Workshop, SMC 2005
Volume2005

Other

Other6th Annual IEEE System, Man and Cybernetics Information Assurance Workshop, SMC 2005
CountryUnited States
CityWest Point, NY
Period6/15/056/17/05

Fingerprint

Learning systems
Classifiers
Intrusion detection

All Science Journal Classification (ASJC) codes

  • Engineering(all)

Cite this

Kang, D. K., Fuller, D., & Honavar, V. (2005). Learning classifiers for misuse and anomaly detection using a bag of system calls representation. In Proceedings from the Sixth Annual IEEE System, Man and Cybernetics Information Assurance Workshop, SMC 2005 (pp. 118-125). [1495942] (Proceedings from the 6th Annual IEEE System, Man and Cybernetics Information Assurance Workshop, SMC 2005; Vol. 2005). https://doi.org/10.1109/IAW.2005.1495942
Kang, Dae Ki ; Fuller, Doug ; Honavar, Vasant. / Learning classifiers for misuse and anomaly detection using a bag of system calls representation. Proceedings from the Sixth Annual IEEE System, Man and Cybernetics Information Assurance Workshop, SMC 2005. 2005. pp. 118-125 (Proceedings from the 6th Annual IEEE System, Man and Cybernetics Information Assurance Workshop, SMC 2005).
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abstract = "In this paper, we propose a {"}bag of system calls{"} representation for intrusion detection in system call sequences and describe misuse and anomaly detection results with standard machine learning techniques on University of New Mexico (UNM) and MIT Lincoln Lab (MIT LL) system call sequences with the proposed representation. With the feature representation as input, we compare the performance of several machine learning techniques for misuse detection and show experimental results on anomaly detection. The results show that standard machine learning and clustering techniques on simple {"}bag of system calls{"} representation of system call sequences is effective and often performs better than those approaches that use foreign contiguous subsequences in detecting intrusive behaviors of compromised processes.",
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Kang, DK, Fuller, D & Honavar, V 2005, Learning classifiers for misuse and anomaly detection using a bag of system calls representation. in Proceedings from the Sixth Annual IEEE System, Man and Cybernetics Information Assurance Workshop, SMC 2005., 1495942, Proceedings from the 6th Annual IEEE System, Man and Cybernetics Information Assurance Workshop, SMC 2005, vol. 2005, pp. 118-125, 6th Annual IEEE System, Man and Cybernetics Information Assurance Workshop, SMC 2005, West Point, NY, United States, 6/15/05. https://doi.org/10.1109/IAW.2005.1495942

Learning classifiers for misuse and anomaly detection using a bag of system calls representation. / Kang, Dae Ki; Fuller, Doug; Honavar, Vasant.

Proceedings from the Sixth Annual IEEE System, Man and Cybernetics Information Assurance Workshop, SMC 2005. 2005. p. 118-125 1495942 (Proceedings from the 6th Annual IEEE System, Man and Cybernetics Information Assurance Workshop, SMC 2005; Vol. 2005).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Kang DK, Fuller D, Honavar V. Learning classifiers for misuse and anomaly detection using a bag of system calls representation. In Proceedings from the Sixth Annual IEEE System, Man and Cybernetics Information Assurance Workshop, SMC 2005. 2005. p. 118-125. 1495942. (Proceedings from the 6th Annual IEEE System, Man and Cybernetics Information Assurance Workshop, SMC 2005). https://doi.org/10.1109/IAW.2005.1495942