  Unmanned aerial vehicles (UAVs) have the potential to establish flexible and
reliable emergency networks in disaster sites when terrestrial communication
infrastructures go down. Nevertheless, potential security threats may occur on
UAVs during data transmissions due to the untrusted environment and open-access
UAV networks. Moreover, UAVs typically have limited battery and computation
capacity, making them unaffordable for heavy security provisioning operations
when performing complicated rescue tasks. In this paper, we develop
RescueChain, a secure and efficient information sharing scheme for UAV-assisted
disaster rescue. Specifically, we first implement a lightweight
blockchain-based framework to safeguard data sharing under disasters and
immutably trace misbehaving entities. A reputation-based consensus protocol is
devised to adapt the weakly connected environment with improved consensus
efficiency and promoted UAVs' honest behaviors. Furthermore, we introduce a
novel vehicular fog computing (VFC)-based off-chain mechanism by leveraging
ground vehicles as moving fog nodes to offload UAVs' heavy data processing and
storage tasks. To offload computational tasks from the UAVs to ground vehicles
having idle computing resources, an optimal allocation strategy is developed by
choosing payoffs that achieve equilibrium in a Stackelberg game formulation of
the allocation problem. For lack of sufficient knowledge on network model
parameters and users' private cost parameters in practical environment, we also
design a two-tier deep reinforcement learning-based algorithm to seek the
optimal payment and resource strategies of UAVs and vehicles with improved
learning efficiency. Simulation results show that RescueChain can effectively
accelerate consensus process, improve offloading efficiency, reduce energy
consumption, and enhance user payoffs.
