Discernment and Diminution of Black Hole Attack in Mobile Ad-Hoc Network using Artificial Intelligence

Abstract

The MANET is an interesting research topic that has movable nodes. The mobile ad hoc system is an important research area. The nodes are connected by wireless connections. Thus it is vital to have a stable network because information and interaction are crucial in diverse fields such as security and catastrophe emergency response. Because of the decentralized system’s vibrant existence, these channels are vulnerable to various threats, including BHA, GHA, SHA. One of the well-known security issues in MANET is the black hole assault. Each node has a routing table containing information from the target node. The number of assaults in MANET is usually protocol networking assaults. The study focused on black hole attacks for discernment and decrease. A black hole attack node wrongly picks up all packet and collects them without passing them to an endpoint by taking a fresh path to the destination nodes. This paper presents BHA defence from assaults with the principle of Artificial Neural Network and calculates its efficiency according to the set of elements, such as efficiency, PDR and delay and energy utilization. This paper aims to devise an artificial neural network method for black hole discernment and reduction in MANET.