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Article Navigation> JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY> 2005> 14(3): 260-263
PENG Xin-guang, LIU Yu-shu, WU Yu-shu, YANG Yong. Classification Model with High Deviation for Intrusion Detection on System Call Traces[J]. JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY, 2005, 14(3): 260-263.
Citation: PENG Xin-guang, LIU Yu-shu, WU Yu-shu, YANG Yong. Classification Model with High Deviation for Intrusion Detection on System Call Traces[J].JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY, 2005, 14(3): 260-263.
shu

Classification Model with High Deviation for Intrusion Detection on System Call Traces

  • 1.

    School of Information Science and Technology, Beijing Institute of Technology, Beijing 100081, China; Department of Computer Science and Technology, Taiyuan University of Technology, Taiyuan030024, China

  • 2.

    School of Information Science and Technology, Beijing Institute of Technology, Beijing 100081, China

  • Received Date:2004-01-08
    Abstract
  • A new classification model for host intrusion detection based on the unidentified short sequences and RIPPER algorithm is proposed. The concepts of different short sequences on the system call traces are strictly defined on the basis of in-depth analysis of completeness and correctness of pattern databases. Labels of short sequences are predicted by learned RIPPER rule set and the nature of the unidentified short sequences is confirmed by statistical method. Experiment results indicate that the classification model increases clearly the deviation between the attack and the normal traces and improves detection capability against known and unknown attacks.
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    • References (8)
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