Optimized Path Planning Strategy to Enhance Security under Swarm of Unmanned Aerial Vehicles

Abstract

Unmanned Aerial Vehicles (UAVs) are widely deployed in military surveillance operations, especially the quadcopter UAVs which are easy to operate and considerably quieter. However, UAVs encounter problems in secure path planning during navigation and are prone to cyber security attacks. Further, due to the UAV battery capacity, the operating time for surveillance is limited. In this paper, we propose a novel Resilient UAV Path Optimization Algorithm (RUPOA) which provides an optimal path under security attacks such as denial-of-service (DoS) and Man-in-the-Middle (MITM) attacks. The performance efficiency of the proposed path planning algorithm is compared with the existing path planning algorithms based on execution time. To achieve secure path planning in UAVs and to mitigate security attacks, a blockchain-aided security solution is proposed. To prevent security attacks, smart contracts are generated where the devices are registered with gasLimit. The blockchain consensus mechanism allows for secure and tamper-free transmission of data between the Ground Control Station (GCS) and a swarm of UAVs. The performance efficiency of the blockchain model is evaluated based on network latency which is the total execution time across the blockchain network.