PRVB: Achieving Privacy-Preserving and Reliable Vehicular Crowdsensing via Blockchain Oracle

Vehicular crowdsensing is attracting more and more attention because of its wide sensing coverage and diverse usage in smart cities. However, privacy issues that stem from traditional vehicular crowdsensing scenarios, violate the participant's privacy. Although some privacy-preserving schemes have been designed that aim to protect the sensitive information of sensed data, the reliability cannot be guaranteed because of the system's centralized structure. The introduction of blockchain in crowdsensing applications provides reliable data storage, however, the reliability of data sources remains an open challenge. Under these circumstances, the crowdsourcing service requester may not be able to obtain quality data. To solve these problems, we propose a novel Privacy-preserving and Reliable Vehicular crowdsensing via Blockchain oracle, called PRVB. More specifically, a privacy-preserving vehicular data aggregation scheme is presented to protect the data privacy and unlinkability between participant vehicles and sensed data. Besides, two protocols are designed to protect data privacy and to achieve fair rewards for data providers. Thorough theoretical analysis and experimental evaluations have proved that the proposed PRVB achieves privacy protection, reliability, and fairness with significant computation & communication efficiency.