Fuzzy Heuristics for Detecting and Preventing Black Hole Attack

Abstract

Mobile Ad-hoc Networks (MANET) is a set of computing nodes with there is no fixed infrastructure support. Every node in the network communicates with one another through wireless links. However, in MANET, the dynamic topology of the nodes is the vital demanding duty to produce security to the network and the black hole attacks get identified and prevented. In this paper, a novel fuzzy inference system is designed for black hole attack detection depending on the node authentication, trust value, Certificate Authority (CA), energy level, and message integrity. Before initiating the route discovery process in MANET, the proposed work mainly concentrates on node authentication. The simulation gets carried out using the Network Simulator (NS2), wherein the fuzzy inference system designed shows better performance by providing a certificate to only the trusted nodes. This helps the malicious nodes detection and prevents the black hole attack. The improvement in Packet Delivery Ratio (PDR) enhances throughput and the end to end delay gets reduced through better performance results. This proves that the system is more reliable and recovered to be used in military applications