Adoption of Cognition for Malicious Node Detection in Homogeneous and Heterogeneous Wireless Networks

Cognitive wireless networks are the solution for the existing networks Infrastructure and security problems for all applications. Cognitive techniques adopted in this paper, monitor the transactions among the nodes in the network and detects the malicious nodes and takes preventive measures. To achieve high detection rate, single-sensing with cognition is adopted and training of network is done using artificial neural network based Supervised learning technique. The proposed concept is implemented for homogeneous and heterogeneous wireless networks. Detection probability is calculated based on the network parameters like, sensing range, node density and broadcast reach ability. As compared with the existing approaches, our proposed approach yielded efficient results.