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Attack Scenario Construction Based on Rule and Fuzzy Clustering

  • Linru Ma
  • Lin Yang
  • Jianxin Wang
Conference paper
  • 190 Downloads
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3802)

Abstract

Correlation of intrusion alerts is a major technique in attack detection to build attack scenario. Rule-based and data mining methods have been used in some previous proposals to perform correlation. In this paper we integrate two complementary methods and introduce fuzzy clustering in the data mining method. To determine the fuzzy similarity coefficients, we introduce a hierarchy measurement and use weighted average to compute total similarity. This mechanism can measure the semantic distance of intrusion alerts with finer granularity than the common similarity measurement . The experimental results in this paper show that using fuzzy clustering method can reconstruct attack scenario which are wrecked by missed attacks.

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References

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    Ning, P., Cui, Y., Reeves, D.S.: Constructing attack scenarios through correlation of intrusion alerts. In: Proceedings of the 9th ACM Conference on Computer and Communications Security, Washington, D.C., pp. 245–254 (2002)Google Scholar
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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Linru Ma
    • 1
  • Lin Yang
    • 2
  • Jianxin Wang
    • 2
  1. 1.School of Electronic Science and EngineeringNational University of Defense TechnologyChangshaChina
  2. 2.Institute of China Electronic System EngineeringBeijingChina

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