Distributed Detection of Attacks in Mobile Ad Hoc Networks Using Learning Vector Quantization

This paper describes the latest results of a research program that is designed to enhance the security of wireless mobile ad hoc networks (MANET) by developing a distributed intrusion detection capability. The current approach uses learning vector quantization neural networks that have the ability to identify patterns of network attacks in a distributed manner. This capability enables this approach to demonstrate a distributed analysis functionality that facilitates the detection of complex attacks against MANETs. The results of the evaluation of the approach and a discussion of additional areas of research is presented.

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