An Intelligent Agent Based Approach for Intrusion Detection and Prevention in Adhoc Networks

This paper describes about an intelligent agent based intrusion detection and prevention system for mobile ad hoc network. This system collects data from application layer and network layer and classifies them using the log file data collected from these layers and local anomalies are computed using local agents finally it is sent to a global agent for integration. The local agents monitor the two layers of the network to determine the correlation among the observed anomalous patterns, reporting such abnormal behavior to the administrator for taking possible action. Our simulation results obtained after integration shows that it is possible to obtain high intrusion-detection rates (99.2%) and low false-alarm rates