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Communication Dans Un Congrès Année : 2011

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

Résumé

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 detec- tion 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.
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Dates et versions

lirmm-00798316 , version 1 (21-03-2019)

Identifiants

Citer

Imen Brahmi, Sadok Ben Yahia, Hamed Aouadi, Pascal Poncelet. Towards a Multiagent-Based Distributed Intrusion Detection System Using Data Mining Approaches. ADMI: Agents and Data Mining Interaction, 2011, Taipei, Taiwan. pp.173-194, ⟨10.1007/978-3-642-27609-5_12⟩. ⟨lirmm-00798316⟩
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