Distributed Agent Based Model for Intrusion Detection System Based on Artificial Immune System

With mounting global network connectivity, the issue of intrusion has achieved importance, promoting active research on efficient Intrusion Detection Systems (IDS). Artificial Immune System (AIS) is a new bio-inspired model which is applied for solving various problems in the field of information security. Because of its unique features, (self-learning, self-adaptation and selfimprovement), AIS has been utilized to design new anomaly base IDS. In this paper we have introduced a new distributed, agent based design of AIS based IDS. In our model detectors are distributed in each host in network while the central engine is located in server which manages the detectors and make final decision about current intrusion based on previous experience of all of the hosts in network. In our purposed model detector agents in each host is actively updated and synchronized with detector agents of other hosts through our IDS’s central engine.

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