BARM: Blockchain-Assisted Anonymous Authentication and Reputation Management for Mobile Crowdsensing in Internet of Vehicles

Abstract

Mobile crowdsensing (MCS) utilizes sensors distributed across different vehicles to support intelligent transportation and environmental monitoring. Recently, most of the research on MCS in Internet of Vehicles (IoV) mainly focuses on privacy protection and data security of anonymous authentication, but there are still shortcomings in reliability evaluation and reputation management of sensing vehicles. Besides, the lack of effective management of identity information may lead to difficulties in tracking malicious behavior. In this article, we propose a blockchain-assisted anonymous authentication and reputation management (BARM) scheme for MCS in IoV. Specifically, an efficient anonymous authentication algorithm is proposed for sensing vehicles. Then, the privacy protection reputation evaluation algorithm is proposed to ensure the reliability of the sensing vehicles and the security of sensing data. Meanwhile, an accurate reputation update algorithm is proposed to effectively check and update the reputation values of participating sensing vehicles. Besides, the smart contracts are written and deployed on the blockchain to manage the information of the sensing vehicles, which improves the security, efficiency, and trust of the identity management. Subsequently, a formal security verification method based on colored petri net (CPN) and Dolev-Yao attacker model is proposed to evaluate the security of the scheme. The evaluation results show that the scheme can effectively resist a variety of different types of attacks and has multiple security attributes. Performance analysis shows that the proposed scheme has low computation and communication overheads and high robustness.