Due to the limited battery and computing resource, offloading unmanned aerial vehicles (UAVs)' computation tasks to ground infrastructure, e.g., vehicles, is a fundamental framework. Under such an open and untrusted environment, vehicles are reluctant to share their computing resource unless provisioning strong incentives, privacy protection, and fairness guarantee. Precisely, without strategy-proofness guarantee, the strategic vehicles can overclaim participation costs so as to conduct market manipulation. Without the fairness provision, vehicles can deliberately abort the assigned tasks without any punishments, and UAVs can refuse to pay by the end, causing an exchange dilemma. Lastly, the strategy-proofness and fairness provision typically require transparent payment/task results exchange under public audit, which may disclose sensitive information of vehicles and make the privacy preservation a foremost issue. To achieve the three design goals, we propose SEAL, an integrated framework to address strategy-proof, fair, and privacy-preserving UAV computation offloading. SEAL deploys a strategy-proof reverse combinatorial auction mechanism to optimize UAVs' task offloading under practical constraints while ensuring economic-robustness and polynomial-time efficiency. Based on smart contracts and hashchain micropayment, SEAL implements a fair on-chain exchange protocol to realize the atomic completion of batch payments and computing results in multi-round auctions. In addition, a privacy-preserving off-chain auction protocol is devised with the assistance of the trusted processor to efficiently protect vehicles' bid privacy. Using rigorous theoretical analysis and extensive simulations, we validate that SEAL can effectively prevent vehicles from manipulating, ensure privacy protection and fairness, improve the offloading efficiency.

翻译：由于电池和计算资源有限，将无人机（UAV）的计算任务卸载至地面基础设施（如车辆）已成为一种基础框架。在开放且不可信的环境中，除非提供强有力的激励、隐私保护和公平性保障，车辆往往不愿共享其计算资源。具体而言，缺少抗策略性保障时，策略性车辆可能虚报参与成本以进行市场操纵；缺少公平性保障时，车辆可无惩罚地中途放弃分配任务，而无人机最终也可拒绝支付，引发交换困境。此外，抗策略性与公平性保障通常需要在公开审计下进行透明的支付/任务结果交换，这可能泄露车辆敏感信息，使隐私保护成为首要问题。为实现上述三个设计目标，我们提出SEAL——一个集成框架，旨在解决无人机计算卸载中的抗策略性、公平性与隐私保护问题。SEAL采用抗策略的反向组合拍卖机制，在确保经济鲁棒性和多项式时间效率的同时，优化无人机在实际约束下的任务卸载。基于智能合约与哈希链微支付，SEAL实现了一种公平的链上交换协议，可在多轮拍卖中原子性完成批量支付与计算结果交换。此外，借助可信处理器设计了隐私保护的链下拍卖协议，以高效保护车辆投标隐私。通过严格理论分析与大量仿真实验，我们验证了SEAL能有效防止车辆操纵、确保隐私保护与公平性，并提升卸载效率。