Enhancing Reliability in Mobile Ad Hoc Networks (MANETs) Through the K-AOMDV Routing Protocol to Mitigate Black Hole Attacks

A Mobile Ad Hoc Network (MANET) is a self-organize assemblage of mobile nodes without the use of pre-existing infrastructure. They face challenges of security, routing efficiency, and network stability due to dynamic topology and limited resources. The Black Hole Attack on MANETs is a critical concern, affecting communication reliability. This malicious activity involves a node falsely advertising the shortest route to the destination, leading data packets to be routed into a “black hole” where they are dropped and causing severe disruptions. This research focuses on the Ad Hoc On-Demand Multi-Path Distance Vector Routing (AOMDV) protocol, which is preferred for its improved efficiency compared to a single-path routing protocol in MANETs. We observe, investigate, and estimate wireless ad-hoc network route optimization by reducing packet hops between nodes. We suggested a novel strategy in this paper, the K-AOMDV protocol that uses K-means clustering to prevent routing misbehavior. The efficiency of the proposed K-AOMDV (KNN-Ad-hoc on demand multi-path distance vector) routing protocol is calculated using supervised machine learning approach to predict optimal routes with delay and attacks. By employing multiple paths and dynamic route discovery, it ensures robust data delivery even in the presence of malicious nodes. This protocol’s adaptability and multi-path nature effectively minimize the effects of Black Hole Attacks, bolstering the MANETs security. Proposed algorithm has a high accuracy rate of 0.99%, 80% true positives, and 80% recall.