z-logo
open-access-imgOpen Access
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.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom