Privacy-Preserving Verifiable Incentive Mechanism for Crowdsourcing Market Applications

Crowd sensing, as a new paradigm that leverages pervasive smartphones to efficiently collect and upload sensing data, recently has been intensively explored. Incentive mechanisms with the truthfulness are proposed to attract extensive users to participate so as to achieve good service quality, enabling numerous novel applications. Although these mechanisms are so promising, there still exist many security and privacy challenges in real-life environments, such as cost privacies, sensing preferences, and the payment behavior of the platform (the crowd sensing application organizer). In this paper, we present two privacy-preserving verifiable incentive mechanisms for crowd sensing applications with homogeneous services, heterogeneous services, and submodular services under the budget constraint, not only to explore how to protect the privacy of the users and platform, but also to ensure the verifiable correctness of payments between the platform and users for crowd sensing applications. Results show that our general privacy-preserving verifiable incentive mechanisms achieve the same results as the generic one without privacy preservation.