Paper Info
Title
A Decentralized Location Privacy-Preserving Spatial Crowdsourcing for Internet of Vehicles
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.
Year
DOI
Venue
2021
10.1109/TITS.2020.3010288
IEEE Transactions on Intelligent Transportation Systems
Keywords
DocType
Volume
Internet of Vehicles,spatial crowdsourcing,location privacy,multi-level privacy-preserving,blockchain
Journal
22
Issue
ISSN
Citations 
4
1524-9050
6
PageRank 
References 
Authors
0.39
0
6
Name
Order
Citations
PageRank
Junwei Zhang1101.79
Fan Yang260.73
Zhuo Ma3235.12
Zhuzhu Wang4103.17
Ximeng Liu513531.84
Jianfeng Ma61336155.62