A Decentralized Location Privacy-Preserving Spatial Crowdsourcing for Internet of Vehicles

【Author】 Zhang, Junwei; Yang, Fan; Ma, Zhuo; Wang, Zhuzhu; Liu, Ximeng; Ma, Jianfeng

【Source】IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS

【影响因子】9.551

【Abstract】With the rapid development of Internet of Vehicles (IoV), vehicle-based spatial crowdsourcing (SC) applications have been proposed and widely applied to various fields. However, location privacy leakage is a serious issue in spatial crowdsourcing because workers who participate in a crowdsourcing task are required to upload their driving locations. In this paper, we propose a decentralized location privacy-preserving SC for IoV, which allows vehicle users to securely participate in SC with ensuring the task's location policy privacy and providing multi-level privacy preservation for workers' locations. Specifically, we introduce blockchain technology into SC, which can eliminate the control of vehicle user data by SC-server. We combine the additively homomorphic encryption and circle-based location verification to ensure the confidentiality of task's location policy. To achieve multi-level privacy preservation for workers' driving locations, we only reveal a grid where workers are located in. The size of the grid represents the level of privacy preservation. We leverage the order-preserving encryption and non-interactive zero-knowledge proof to prevent workers from illegally obtaining rewards by forging their driving locations. The security analysis results show that our framework can satisfy the above requirements. In addition, the experiment results demonstrate that our framework is efficient and feasible in practice.

【Keywords】Task analysis; Privacy; Encryption; Crowdsourcing; Data privacy; Internet of Vehicles; spatial crowdsourcing; location privacy; multi-level privacy-preserving; blockchain

【发表时间】2021 APR

【收录时间】2022-01-02

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