Using boosting learning method for intrusion detection

Authors:
Wu Yang;Xiao-Chun Yun;Yong-Tian Yang
Affiliations:
Information Security Research Center, Harbin Engineering University, Harbin, China;Information Security Research Center, Harbin Engineering University, Harbin, China;Information Security Research Center, Harbin Engineering University, Harbin, China
Venue:
ADMA'05 Proceedings of the First international conference on Advanced Data Mining and Applications
Year:
2005

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Abstract

It is an important research topic to improve detection rate and reduce false positive rate of detection model in the field of intrusion detection. This paper adopts an improved boosting method to enhance generalization performance of intrusion detection model based on rule learning algorithm, and presents a boosting intrusion detection rule learning algorithm (BIDRLA). The experiment results on the standard intrusion detection dataset validate the effectiveness of BIDRLA.