ACBFT: Adaptive Chained Byzantine Fault-Tolerant Consensus Protocol for UAV Ad Hoc Networks
Jingjing Wang, Jiaxing Wang, Z. Tong, Zihan Jiao, Mengyuan Zhang, Chunxiao Jiang
Abstract
The integration of blockchain technology with uncrewed aerial vehicles (UAVs) presents significant potential, offering prospects for enhanced cybersecurity and fostering innovation within the UAV industry. As the foundation of blockchain technology, the consensus protocol determines system performance and security. However, the high mobility and limited resources of UAVs render traditional consensus protocols, which require substantial resources, unsuitable for UAV networks. The dynamic nature of UAVs results in topology changes, further exacerbating the network environment's complexity. Therefore, we propose an adaptive chained byzantine fault tolerance (ACBFT) protocol tailored specifically for UAV network environments. This protocol utilizes the particle swarm optimization (PSO) algorithm to optimize the chain consensus process, enhancing robustness and reducing communication overhead. In addition, we propose several sub-protocols to assist ACBFT in handling unexpected situations, including the rechaining protocol for managing malicious nodes, joining and exiting protocols for dynamic nodes, and strategies for handling accident situations such as UAV loss. Our security analysis and performance evaluations demonstrate that ACBFT not only increases throughput and reduces communication overhead, but also ensures security and efficiency.