A Secure and Efficient Data Sharing Scheme for UAV Networks: Integration of Blockchain and Prospect Theory

Empowered by crowdsensing technology, unmanned aerial vehicles (UAVs) equipped with rich sensors can perform sensing tasks in extreme scenarios. However, due to the selfishness and distrust of UAVs, some malicious UAVs with insufficient resources may provide false sensing data to the task publishers. In addition, the centralized sensing platform is vulnerable to various attacks (e.g., data tampering attacks and single point of failure) in traditional crowdsensing, resulting in degraded data quality and severe security issues. To cope with these problems, we propose a blockchain-based crowdsensing framework with reputation incentive (BCFR) for UAV-assisted mobile crowdsensing. Specifically, a reputation-based incentive scheme is first proposed to relate the behavior of each UAV with its reputation, and then to choose UAVs with high reputation to perform sensing tasks, thereby improving the security of sensing data sharing. Afterwards, we design a blockchain-based secure data transmission scheme to securely record data transactions of UAVs. Furthermore, UAVs may be reluctant to perform compute-intensive mining tasks due to their limited computing capabilities. Therefore, a two-stage Stackelberg game is introduced to motivate UAVs to participate in the block creation process. In a more realistic scenario, where participants are bounded rational, prospect theory (PT) is utilized to capture the potential subject perceptions of UAVs. Finally, simulation results and security analysis demonstrate that the proposed BCFR scheme can effectively improve the probability of successful mining and ensure the security of data sharing.