Intrusion Detection Using Variable-Length Audit Trail Patterns
Author(s) -
Andreas Wespi,
Marc Daciér,
Hervé Debar
Publication year - 2000
Publication title -
lecture notes in computer science
Language(s) - English
Resource type - Book series
SCImago Journal Rank - 0.249
H-Index - 400
eISSN - 1611-3349
pISSN - 0302-9743
ISBN - 3-540-41085-6
DOI - 10.1007/3-540-39945-3_8
Subject(s) - computer science , intrusion detection system , variable (mathematics) , unix , testbed , process (computing) , system call , data mining , table (database) , construct (python library) , algorithm , software , mathematics , operating system , programming language , mathematical analysis , computer network
Audit trail patterns generated on behalf of a Unix process canb e used to model the process behavior. Most of the approaches proposed so far use a table of fixed-length patterns to represent the process model. However, variable-length patterns seem to be more naturally suited to model the process behavior, but they are also more difficult to construct. In this paper, we present a novel technique to build a table of variable-length patterns. This technique is based on Teiresias, an algorithm initially developed for discovering rigid patterns in unaligned biological sequences. We evaluate the quality of our technique in a testbed environment, and compare it with the intrusion-detection system proposed by Forrest et al. [8], which is based on fixed-length patterns. The results achieved with our novel method are significantly better than those obtained with the original method based on fixed-length patterns.
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