SRSP: A Secure and Reliable Smart Parking Scheme with Dual Privacy Preservation

Finding an empty parking lot in a downtown or busy area is difficult and time-consuming. Smart parking services enable vehicles to obtain real-time parking information, which has great potential to mitigate the parking problem. Compared with the existing parking methods, the cooperative parking information sharing based on vehicular crowdsourcing has lower cost and higher accuracy. However, vehicles face the threat of identity and trajectory privacy leakage. In order to provide secure and reliable parking service, we propose a secure and reliable smart parking scheme with dual privacy preservation. Specifically, a novel group signature technique can be equipped to achieve anonymous authentication among vehicles, parking server, and fog node. Meanwhile, the mix zone method combined with differential privacy can be utilized to hide the vehicles’ trajectory. Moreover, message-lock encryption technique enables fog node to detect and delete duplicated reports to reduce the computational overhead of parking server. An incentive mechanism is proposed, which can not only reward contributing vehicles, but also prevent the same vehicle from getting multiple rewards. In addition, the trust model is designed to evaluate the reliability of vehicles based on direct trust and recommendation trust. Finally, security analysis demonstrates that SRSP can achieve security objectives. Performance evaluation shows that SRSP has lower computational overhead compared with the existing schemes.