Title
Exploiting Pattern Relationship For Intrusion Detection
Keywords
Aggregates; Application software; Computer science; Data mining; Data preprocessing; Internet; Intrusion detection; Pattern matching; Protection; Testing
Abstract
The problem of identifying patterns from system call trails of UNIX processes to better model application behavior has been investigated intensively. Most existing approaches focus on capturing the relationship between individual system calls (or system audit events). We add one additional dimension to the problem domain by also taking into consideration the overlap relationship between patterns. We first present a pattern extraction algorithm to generate maximal patterns from system call trails. Overlap relationship between patterns is subsequently investigated and stored Finally, both maximal patterns and their relationships are exploited to detect deviations from normal application behavior. We test this idea using the popular sendmail data set and the login data set obtained from the University of New Mexico. Experimental results indicate that our scheme achieves a much higher detection rate than systems that only consider intra-pattern relationship while maintaining a very low false alarm rate with similar space and time efficiency.
Publication Date
1-1-2003
Publication Title
Proceedings - 2003 Symposium on Applications and the Internet, SAINT 2003
Number of Pages
200-208
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1109/SAINT.2003.1183049
Copyright Status
Unknown
Socpus ID
60349129462 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/60349129462
STARS Citation
Jiang, Ning; Hua, K. A.; and Oh, Jung Hwan, "Exploiting Pattern Relationship For Intrusion Detection" (2003). Scopus Export 2000s. 1987.
https://stars.library.ucf.edu/scopus2000/1987