  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.
