A Privacy-Preserving Traffic Monitoring Scheme via Vehicular Crowdsourcing
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School of Computer Science and Technology, Beijing Institute of Technology, Beijing 100081, China
2
Department of Computer and Information Sciences, Temple University, Philadelphia, PA 19122, USA.
3
Department of Computer Science and Engineering, Qatar University, Doha 2713, Qatar
*
Authors to whom correspondence should be addressed.
Sensors 2019, 19(6), 1274; https://doi.org/10.3390/s19061274
Received: 3 February 2019
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Revised: 1 March 2019
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Accepted: 2 March 2019
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Published: 13 March 2019
(This article belongs to the Special Issue Future Research Trends in Internet of Things and Sensor Networks)
The explosive number of vehicles has given rise to a series of traffic problems, such as traffic congestion, road safety, and fuel waste. Collecting vehicles’ speed information is an effective way to monitor the traffic conditions and avoid vehicles’ congestion, however it may threaten vehicles’ location and trajectory privacy. Motivated by the fact that traffic monitoring does not need to know each individual vehicle’s speed and the average speed would be sufficient, we propose a privacy-preserving traffic monitoring (PPTM) scheme to aggregate vehicles’ speeds at different locations. In PPTM, the roadside unit (RSU) collects vehicles’ speed information at multiple road segments, and further cooperates with a service provider to calculate the average speed information for every road segment. To preserve vehicles’ privacy, both homomorphic Paillier cryptosystem and super-increasing sequence are adopted. A comprehensive security analysis indicates that the proposed PPTM can preserve vehicles’ identities, speeds, locations, and trajectories privacy from being disclosed. In addition, extensive simulations are conducted to validate the effectiveness and efficiency of the proposed PPTM scheme.
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Keywords:
traffic monitoring; speed; privacy-preserving; vehicular crowdsourcing
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MDPI and ACS Style
Zhang, C.; Zhu, L.; Xu, C.; Du, X.; Guizani, M. A Privacy-Preserving Traffic Monitoring Scheme via Vehicular Crowdsourcing. Sensors 2019, 19, 1274. https://doi.org/10.3390/s19061274
AMA Style
Zhang C, Zhu L, Xu C, Du X, Guizani M. A Privacy-Preserving Traffic Monitoring Scheme via Vehicular Crowdsourcing. Sensors. 2019; 19(6):1274. https://doi.org/10.3390/s19061274
Chicago/Turabian StyleZhang, Chuan, Liehuang Zhu, Chang Xu, Xiaojiang Du, and Mohsen Guizani. 2019. "A Privacy-Preserving Traffic Monitoring Scheme via Vehicular Crowdsourcing" Sensors 19, no. 6: 1274. https://doi.org/10.3390/s19061274
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