PARS: Privacy-Aware Reward System for Mobile Crowdsensing Systems

Crowdsensing systems have been developed for wide-area sensing tasks because humancarried smartphones are prevailing and becoming capable. To encourage more people to participate in sensing tasks, various incentive mechanisms were proposed. However, participating in sensing tasks and getting rewards can inherently risk the users' privacy and discourage their participation. In particular, the rewarding process can expose the participants' sensor data and possibly link sensitive data to their identities. In this work, we propose a privacy-preserving reward system in crowdsensing using the blind signature. The proposed scheme protects the participants' privacy by decoupling contributions and rewarding claims. Our experiment results show that the proposed mechanism is feasible and efficient.