A probabilistic method for detecting anomalous program behavior

Kohei Tatara, Toshihiro Tabata, Kouichi Sakurai

Research output: Contribution to journalConference articlepeer-review


In this paper, we, as well as Eskin, Lee, Stolfo propose a method of prediction model. In their method, the program was characterized with both the order and the kind of system calls. We focus on a non-sequential feature of system calls given from a program. We apply a Bayesian network to predicting the N-th system call from the sequence of system calls of the length N - 1. In addition, we show that a correlation between several kinds of system calls can be expressed by using our method, and can characterize a program behavior.

Original languageEnglish
Pages (from-to)87-98
Number of pages12
JournalLecture Notes in Computer Science
Publication statusPublished - 2005
Event5th International Workshop on Information Security Applications, WISA 2004 - Jeju Island, Korea, Republic of
Duration: Aug 23 2004Aug 25 2004

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science


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