An Efficient Methodology for Detecting Malicious Nodes in Cognitive Radio Networks

An efficient malicious node detection system in CR networks is proposed in this paper. This proposed system contains features extraction process and optimization algorithm with soft computing framework. This proposed methodology stated in this paper initially abstracts the features of each individual node in CR network and these individual features are now getting optimized using feed forward radial neural network algorithm, which differentiates each individual node in CR network into either normal or malicious/faulty. This paper analyzes the performance of this proposed work with respect to malicious node detection rate, throughput and latency.