Enhancing Adversary Identification in UAV Networking using Piggybacking AODV Protocol

In today’s world, Unmanned Aerial Vehicles (UAVs) are becoming increasingly common in wireless networks. With this rise comes the urgent need for strong security measures to protect against potential threats. While there are existing studies on detecting and dealing with attacks, one challenge remains: how to proactively identify compromised UAV nodes. In this paper, we provide a novel method termed Piggybacking AODV. The routing protocol Adhoc On-Demand Distance Vector (AODV) is utilized in this technique to effectively identify hacked UAV nodes in wireless networks. Our approach cleverly adds detection mechanisms to AODV routing messages, reducing overhead and seamlessly integrating with existing network protocols. Our solution leverages multi-path routing protocols along with cheating identification schemes and secret sharing to identify compromised UAV nodes without requiring centralized authority or trusted third-party nodes. Moreover, our solution ensures quiet identification, making it difficult for sophisticated adversaries to disrupt the detection process. Through rigorous analysis and extensive simulation experiments, we show that Piggybacking AODV is effective and feasible. With the least amount of communication overhead and detection times, improve both the detection and message delivery rates. Overall, this result introduces a promising way to enhance security in UAV-enabled wireless networks. This approach strengthens network resilience and is compatible with existing infrastructure, clearing the path for dependable and safe UAV services across a range of uses. Keywords: Applications for Vehicle Networks, Ad Hoc Networks, UAVS, and VANETs.