DYNAMIC NEURAL NETWORKS IN THE DETECTION OF DISTRIBUTED ATTACKS IN MOBILE AD-HOC NETWORKS
James Cannady
Graduate School of Computer and Information Sciences, Nova Southeastern University, Fort Lauderdale, FL, USA
ABSTRACT
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.
KEYWORDS
Mobile ad-hoc networks, intrusion detection, neural networks
Original Source Link : http://airccse.org/journal/nsa/1010s1.pdf
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