AnoPay: Anonymous Payment for Vehicle Parking With Updatable Credential

Abstract

Many existing anonymous parking payment schemes lack high efficiency and flexibility. For instance, the calculation and communication costs involved in payment may linearly increase with the payment amount. In this paper, we propose an anonymous payment system (dubbed AnoPay) for vehicle parking, which leverages updatable attribute-based anonymous credentials and efficient zero-knowledge proof (ZKP) to achieve user anonymity and constant overhead for parking fee payment. To further improve the efficiency, we design a secure parking fee aggregation protocol based on linear homomorphic encryption to aggregate parking transactions, where the amount of each parking transaction is hidden and the privacy of the parking lot in terms of its revenue is guaranteed. AnoPay achieves both unlinkability and accountability, malicious payments can be efficiently traced when it is necessary. We provide a security model and rigorous proof for each security property of AnoPay. Extensive experiments and comparisons demonstrate the efficiency and practicality of the system.