Towards a multiagent-based distributed intrusion detection system using data mining approaches
ADMI'11 Proceedings of the 7th international conference on Agents and Data Mining Interaction
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This paper describes a multiagent system with capabilities to analyze and discover knowledge gathered from distributed agents. These enhanced capabilities are obtained through a dynamic self-organizing map and a multiagent communication system. The central administrator agent dynamically obtains information about the attacks or intrusions from the distributed agents and maintains a knowledge pool using a proposed growing self-organizing map. The approach integrates traditional mathematical and data mining techniques with a multiagent system. The proposed system is used to build an intrusion detection system (IDS) as a network security application. Finally, experimental results are presented to confirm the good performance of the proposed system.