A Combination of Signature-based IDS and Machine Learning-based IDS using Alpha-cut and Beta pick


KIPS Transactions on Computer and Communication Systems, Vol. 12, No. 4, pp. 609-616, Aug. 2005
10.3745/KIPSTC.2005.12.4.609,   PDF Download:

Abstract

Signature-based Intrusion Detection has many false positive and many difficulties to detect new and changed attacks. Alpha-cut is introduced which reduces false positive with a combination of signature-based IDS and machine signature-based IDS in prior paper [1]. This research is a study of a succession of Alpha-cut, and we introduce Beta-pick in which attacks can be detected but cannot be detected in single signature-based detection. Alpha-cut is a way of increasing detection accuracy for the signature based IDS, Beta-pick is a way which decreases the case of treating attack as normality. For Alpha-cut and Beta-pick we use XIBL as a learning algorithm and also show the difference of result of C4.5. To describe the value of proposed method we apply Alpha-cut and Beta-pick to signature-based IDS and show the decrease of false alarms.


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Cite this article
[IEEE Style]
I. Y. Weon, D. H. Song and C. H. Lee, "A Combination of Signature-based IDS and Machine Learning-based IDS using Alpha-cut and Beta pick," KIPS Journal C (2001 ~ 2012) , vol. 12, no. 4, pp. 609-616, 2005. DOI: 10.3745/KIPSTC.2005.12.4.609.

[ACM Style]
Ill Young Weon, Doo Heon Song, and Chang Hoon Lee. 2005. A Combination of Signature-based IDS and Machine Learning-based IDS using Alpha-cut and Beta pick. KIPS Journal C (2001 ~ 2012) , 12, 4, (2005), 609-616. DOI: 10.3745/KIPSTC.2005.12.4.609.