A Two-Stage Secure Incentive Mechanism in App-and UAV-Assisted Crowdsensing

Abstract

Unmanned aerial vehicles (UAVs) combined with tagging applications (Apps) have recently attracted considerable attention to enable efficient mobile crowdsensing (MCS) applications in scenarios where an insufficient number of UAVs may be available to perform the sensing tasks. However, there remain potential security and incentive threats for App- and UAV-assisted crowdsensing owing to the presence of malicious UAVs and the selfishness of UAVs. To address these issues, we propose a two-stage secure incentive mechanism in the App- and UAV-assisted MCS. Specifically, we first develop an App- and UAV-assisted MCS framework, where the App tags the location of the sensing task as a point-of-interest (PoI) to attract registered UAVs, thus assisting the platform to complete the sensing task efficiently. To motivate the App to cooperate with the sensing platform, we design a double auction-based incentive mechanism for PoI-tagging tasks in the first stage, where the optimal price for PoI-tagging services is obtained by applying a double auction game. Furthermore, we evaluate each UAV through comprehensive consideration of the performance and security of UAVs for most task-suitable UAV recruitment and malicious UAVs prevention. Additionally, in the second stage, based on the Stackelberg game theory, an incentive mechanism for sensing tasks is proposed to encourage UAV participation. Finally, simulation results and security analysis validate that the proposed mechanism can greatly increase the utility of UAVs and the App while ensuring the security of the sensing process.