Black hole detection using evolutionary algorithm for IDS/IPS in MANETs

Mobile ad hoc network (MANET) is a self organized structure of mobile nodes which are distributed unevenly in the environment. There are various MANET routing protocols exist which cannot stand against the security issues which might occur inside or outside of the MANET environment. Black hole attack is most popular insider attack happening on the MANET environment which needs to be concerned more to avoid the unwanted packet loss. These problems are resolved in the proposed research method by introducing new method namely hybridization of particle swarm optimization with genetic algorithm (HPSO-GA) routing system. The main contribution of this research method is to detect the black hole attack (BHA) by utilizing ad hoc on demand distance vector (AODV) routing protocol. This method utilizes the data routing information (DRI) of the neighbouring nodes instead of considering source node information. DRI information are gathered from every neighbouring nodes which increases the probability of attack detection accuracy. The suggested HPSO-GA routing mechanism researches the black hole attack in MANET, at that point, the outputs were measured utilizing the parameters namely detection rate, false positive alarm (FPA), packet delivery ratio (PDR), routing overhead, average end to end delay and throughput. The outcomes are contrasted with existing techniques, like, AODV, local intrusion detection (LID) with AODV. Simulation output utilizing the network simulator demonstrates that the improvement ratio of the throughput picked up by HPSO-GA security routing mechanism and general improvement reduction at end-to-end delay and routing overhead.