Abstract
Learning Classifier Systems (LCS) have previously been shown to have application in Intrusion Detection. This paper extends work in the area by applying the Self-Organizing Map (SOM) for creating the new input string by 2-bit encoding rely on degree of deviation of normal behaviour. The performance of systems is investigated under an FTP-only dataset. It is shown that the proposed system is able to perform significantly better than the conventional XCS, modified XCS and twelve ML algorithms.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Debar, H., Dacier, M., Wepspi, A.: A revised taxonomy for intrusion 590 detection systems. Technical report, Computer Science/Ma- 591 thematics (1999)
Frank, J.: Artificial Intelligence and Intrusion Detection: Current and future directions. In: Proceedings of the 17th National Computer Security Conference (October 1994)
Wilson, S.W.: Classifier Fitness Based on Accuracy. Evolutionary Computation 3(2), 149–176 (1995)
Holland, J.H.: Adaptation. In: Rosen, Snell (eds.) Progress in Theoretical Biology (1976)
Bull, L. (ed.): Applications of Learning Classifier Systems. Springer, Heidelberg (2004)
Shafi, K., Kovacs, T., Abbass, H.A., Zhu, W.: Intrusion detection with evolutionary learning classifier systems. Natural Computing (December 2007)
Hettich, S., Bay, S.D.: The UCI KDD Archive (1999), http://www.kdd.ics.uci.edu
Kohonen, T.: Self-organization and associative memory. Springer, New York (1989)
Butz, M., Wilson, S.: An algorithmic descriptionof XCS. In: Lanzi, P.L., Stolzmann, W., Wilson, S.W. (eds.) IWLCS 2000. LNCS, vol. 1996, pp. 253–272. Springer, Heidelberg (2001)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Tamee, K., Rojanavasu, P., Udomthanapong, S., Pinngern, O. (2008). Using Self-Organizing Maps with Learning Classifier System for Intrusion Detection. In: Ho, TB., Zhou, ZH. (eds) PRICAI 2008: Trends in Artificial Intelligence. PRICAI 2008. Lecture Notes in Computer Science(), vol 5351. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89197-0_109
Download citation
DOI: https://doi.org/10.1007/978-3-540-89197-0_109
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-89196-3
Online ISBN: 978-3-540-89197-0
eBook Packages: Computer ScienceComputer Science (R0)