Construction of Finite Automata for Intrusion Detection from System Call Sequences by Genetic Algorithms

Intrusion detection systems protect normal users and system resources from information security threats. Anomaly detection is an approach of intrusion detection that constructs models of normal behavior of users or systems and detects the behaviors that deviate from the model. Monitoring the sequenc...

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Bibliographic Details
Published inAdvances in Knowledge Discovery and Data Mining pp. 594 - 602
Main Authors Wee, Kyubum, Kim, Sinjae
Format Book Chapter Conference Proceeding
LanguageEnglish
Published Berlin, Heidelberg Springer Berlin Heidelberg 2006
Springer
SeriesLecture Notes in Computer Science
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Summary:Intrusion detection systems protect normal users and system resources from information security threats. Anomaly detection is an approach of intrusion detection that constructs models of normal behavior of users or systems and detects the behaviors that deviate from the model. Monitoring the sequences of system calls generated during the execution of privileged programs has been known to be an effective means of anomaly detection. Finite automata have been recognized as an appropriate device to model normal behaviors of system call sequences. However, there have been several technical difficulties in constructing finite automata from sequences of system calls. We present our study on how to construct finite automata from system call sequences using genetic algorithms. The resulting system is shown to be very effective in detecting intrusions through various experiments.
ISBN:9783540332060
3540332065
ISSN:0302-9743
1611-3349
DOI:10.1007/11731139_69