ASAP: An Anonymous Smart-Parking and Payment Scheme in Vehicular Networks

Abstract

Cruising for a vacant and economical parking spot causes not only time-consuming and frustrating driving experiences, but fuel waste and air pollution. Public parking spots in crowded cities are scarce and expensive. On the contrary, private parking spots usually have low utilization rates, and the spot suppliers are willing to provide their extra parking resources due to a maintenance cost by charging parking fees. Given this situation, it is imperative to call for a smart parking system that collects and provides private parking spots (e.g., around home or workplace) to ease public parking concerns. However, when the suppliers (drivers) are providing (querying for) parking spots, their privacy (e.g., location, identity) is inevitable to be disclosed and existing parking schemes cannot achieve anonymous authentication and anonymous payment simultaneously. To tackle these problems, we propose an anonymous smart-parking and payment (ASAP) scheme in vehicular networks. Specifically, we use short randomizable signature to provide anonymity and conditional privacy. We achieve quick result matching with hashmap and anonymous payment with E-cash. Security analysis and experimental results show that ASAP can protect privacy in a conditional way and has low computational costs and communication overhead.