A Secure and Robust Blockchain-Based Identity Management Scheme Oriented to UAV Network

Unmanned Aerial Vehicle (UAV) networks are increasingly used in scenarios such as power inspection, agricultural plant protection, and emergency rescue. These scenarios often suffer from a deficiency of robust infrastructure, which can result in decentralized security challenges in UAV identity management. Some blockchain-based schemes have been proposed to construct distributed trust mechanisms that do not rely on centralized infrastructure. However, these schemes have yet to address the security of UAV reconnection and the task integrity protection following disconnections. Moreover, the integration of blockchain technology introduces severe resource overhead, decreasing the operational endurance of UAVs and extending management latency. In this paper, we present a scheme for a distributed UAV network based on blockchain technology to ensure secure identity management. Our scheme includes a secure UAV reconnection protocol, task result backup method, and a lightweight blockchain framework. Specifically, the reconnection protocol employs a hybrid authentication approach that combines intrinsic system characteristics with test task behavior, ensuring both the security of UAV reconnection authentication and the robustness of the UAV cluster. The backup method guarantees the integrity of task results even when any disconnection occurs, by redundantly storing results in both the head UAV and a member UAV. We construct a lightweight blockchain framework by eliminating energy-intensive mining processes and simplifying on-chain operations, thereby reducing resource consumption. We utilize the Universally Composable (UC) security model to prove that our scheme can resist the attacks proposed, and we theoretically analyze the consensus process of our lightweight blockchain, showing that it is more streamlined compared to the mainstream blockchain Fabric. Simulation results demonstrate that our scheme exhibits superior robustness and task integrity. Our scheme reduces the average consensus latency by over 60% compared to the Fabric, and at peak times, it requires only 60% of the CPU utilization compared to Fabric.