A Secure and Privacy Preserving Incentive Mechainism for Vehicular Crowdsensing with Data Quality Assurance
Fan Li, Xiaoru Li, Yuchuan Fu, Pincan Zhao, Sha Liu · 2021 IEEE 94th Vehicular Technology Conference (VTC2021-Fall) · 2021
With the development of communication and Internet of Vehicles (IoV) technology, a large number of high precision sensors and computing units are widely used and deployed on vehicles. With the vehicles work as users, Mobile Crowdsensing (MCS) system has a broad application prospect in traffic planning, environmental monitoring and so on. The realization of these applications needs a large amount of data. However, in the process of crowdsensing, users are often faced with the consumption of computing, communication and energy and the risk of privacy leakage, so they are reluctant to actively participate. Therefore, we need to design a safe and reasonable incentive mechanism. In this paper, we focus on privacy protection and user incentive, and propose a framework of the vehicular crowdsensing with blockchain, as well as the smart contacts deployed on the blockchain. The characteristics of the blockchain are used to solve the security problems in the crowdsensing process. In addition, we propose a reverse auction-based incentive mechanism. A group of users with the highest reputation value are selected to complete the sensing tasks, and the payoffs are assigned according to the quality of the sensing data uploaded by the selected users. Finally, Matlab-based simulation verifies the effectiveness of the incentive mechanism proposed in this paper.