Abstract
Attack Detection in a tactical mobile ad-hoc network (MANET) environment is a daunting task due to its wide open and dynamic characteristics. In the battlefield arena the use of peer-to-peer wireless ad-hoc networks by the army bestow a multitude of vulnerabilities within the network that may prove detrimental to the users of that system. Preliminary studies have shown that traditional approaches to intrusion detection may be inadequate for effective detection in an environment with dropping nodes and rapidly changing network topologies stemming from node movements. This study shows a distributed attack detection approach for a tactical MANET using intelligent agents equipped with inference systems based on fuzzy logic. The results produce a prototype intrusion detection system capable of effectively detecting attacks in a tactical MANET with accuracy approaching 95%. The attack recognition system is implemented using stationary intelligent fuzzy agents (SIFA) resident on each node. Agents run autonomously on each node, collect packets from the data stream, extract relevant information, exchange information through light-weight messages, and trigger alerts using the fuzzy inference process. The research was conducted in two phases. First, the environment was characterized and analyzed for which a representative data set was produced. Secondly, the SIFA application was developed and tested on the dataset. The results suggest a successful technique for performing intrusion detection in a dynamic tactical MANET.
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