Adaptive fuzzy inference system for detection and prevention of cooperative black hole attack in MANETs

A MANET (mobile adhoc network) is a group of computing nodes or cell or other devices used for communication which are capable of communication among each other with no support of an infrastructure that is fixed. MANET in fact is selfsufficient group of cellular consumers which talk to each other with the help of cellular nodes, described by certain wireless links. In these applications, in order to offer quality services for MANETs, many routing protocols have been designed. In this paper, a novel method that detects and prevents the supportive black hole attack on MANETs is developed. The proposed method is based on adaptive fuzzy inference system for MANET in order to detect and prevent the cooperative black hole attack. The popular protocol utilized in MANET is on-demand distance vector (AODV) protocol, and is simulated using NS2. The simulated results of the proposed method are compared with that of an adaptive method [17], wherein source node checks all nodes activity by using DAT table that maintains from-node-to-next-node's information and declares black hole node by channel overhearing method. It is observed that the proposed method based on adaptive fuzzy logic system shows better performance as compared to adaptive method in terms of throughput, end-to-end delay and packet delivery ratio.