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Towards a Multiagent-Based Distributed Intrusion Detection System Using Data Mining Approaches

  • Imen Brahmi
  • Sadok Ben Yahia
  • Hamed Aouadi
  • Pascal Poncelet
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7103)

Abstract

The system that monitors the events occurring in a computer system or a network and analyzes the events for sign of intrusions is known as Intrusion Detection System (IDS). The IDS need to be accurate, adaptive, and extensible. Although many established techniques and commercial products exist, their effectiveness leaves room for improvement. A great deal of research has been carried out on intrusion detection in a distributed environment to palliate the drawbacks of centralized approaches. However, distributed IDS suffer from a number of drawbacks e.g., high rates of false positives, low efficiency, etc. In this paper, we propose a distributed IDS that integrates the desirable features provided by the multi-agent methodology with the high accuracy of data mining techniques. The proposed system relies on a set of intelligent agents that collect and analyze the network connections, and data mining techniques are shown to be useful to detect the intrusions. Carried out experiments showed superior performance of our distributed IDS compared to the centralized one.

Keywords

Intrusion Detection System Multi-agents Misuse Detection Anomaly Detection Data Mining Techniques 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Imen Brahmi
    • 1
  • Sadok Ben Yahia
    • 1
  • Hamed Aouadi
    • 2
  • Pascal Poncelet
    • 3
  1. 1.Faculty of Sciences of TunisTunisia
  2. 2.ISLAIBBejaTunisia
  3. 3.LIRMM UMR CNRS 5506MontpellierFrance

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