PAID: Privacy-Preserving Incentive Mechanism Based on Truth Discovery for Mobile Crowdsensing

Incentive mechanisms are an essential method to encourage users to participate in the mobile crowdsensing task. However, most incentive mechanisms based on data quality do not consider users’ security and privacy protection. To overcome the above problems, we propose a privacy protection incentive mechanism based on truth discovery, named PAID. Specifically, we use the secure truth discovery scheme to calculate ground truth and the weight of users’ data while protecting their privacy. Besides, to ensure the accuracy of the MCS results, a data eligibility assessment is proposed to remove unreliable user data before the truth discovery scheme. Finally, we distribute rewards to users based on their data quality. The analysis and evaluation demonstrate the security and effectiveness of our PAID.