Toward Privacy-Preserving Valet Parking in Autonomous Driving Era

Abstract

Automated valet parking, deemed as a key milestone on the way to autonomous driving, has great potential to improve the “last-mile” driving experience for users. On the other hand, it triggers serious risks on vehicle theft and location privacy leakage. To address these issues, we propose a secure and privacy-preserving automated valet parking protocol for self-driving vehicles. The proposed protocol is characterized by extending anonymous authentication to support two-factor authentication with mutual traceability for reducing the risks of vehicle theft and preventing the privacy leakage of users in automated valet parking. Specifically, based on one-time password and secure mobile devices, two-factor authentication is achieved between vehicles and smartphones to ensure vehicle security in remote pickup. By exploiting the BBS+ signature and the Cuckoo filter, user location privacy is protected against the curious parking lots and service providers. In addition, the traceable tags are designed to enable a trusted authority to identify the vehicles and users for localizing a stolen or missing vehicle and preventing the slandering of greedy users. Finally, formal security analysis on the proposed protocol is given to show that the authentication, anonymity, and traceability can be reduced to standard hard assumptions, and performance evaluation demonstrates the proposed protocol is efficient and practical to be implemented in autonomous driving era.