Using Boosting Learning Method for Intrusion Detection

  • Wu Yang
  • Xiao-Chun Yun
  • Yong-Tian Yang
Conference paper

DOI: 10.1007/11527503_75

Part of the Lecture Notes in Computer Science book series (LNCS, volume 3584)
Cite this paper as:
Yang W., Yun XC., Yang YT. (2005) Using Boosting Learning Method for Intrusion Detection. In: Li X., Wang S., Dong Z.Y. (eds) Advanced Data Mining and Applications. ADMA 2005. Lecture Notes in Computer Science, vol 3584. Springer, Berlin, Heidelberg

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.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Wu Yang
    • 1
  • Xiao-Chun Yun
    • 1
    • 2
  • Yong-Tian Yang
    • 1
  1. 1.Information Security Research CenterHarbin Engineering UniversityHarbinChina
  2. 2.Computer Network and Information Security Technique Research CenterHarbin Institute of TechnologyHarbinChina

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