SPIR: A Secure and Privacy-Preserving Incentive Scheme for Reliable Real-Time Map Updates

Abstract

The high-precision maps can provide additional information on roads and conditions, which plays an important role in autonomous vehicles (AVs) navigation. Compared with the existing map update methods, the real-time map updates based on crowdsensing have lower cost and higher accuracy. However, in the process of map update, the map service platform (MSP) cannot recruit enough vehicle users to obtain the sensing data due to a lack of incentive mechanism. Therefore, how to motivate more vehicle users to provide high-quality sensing data is the key for real-time map updates. In this article, we propose a secure and privacy-preserving incentive scheme for reliable real-time map updates, named SPIR. Specifically, under the condition of limited service platform budget and limited vehicle user’s ability, an effective incentive mechanism based on reverse auction is presented, which can solve two core problems: i.e., payment control for MSP and completion quality for vehicle users. Meanwhile, a credit management and payment system based on the blockchain technique are designed. In addition, the partially blind signature technique is applied to guarantee the security of the incentive mechanism and protect the privacy of vehicle users. Both theoretical analysis and simulation results indicate that the proposed SPIR achieves near-optimal benefits, which can provide the fair reward for vehicle users and reasonable budget for the MSP. In the real-time map update services, SPIR can guarantee the computational efficiency and data reliability.