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Sensors 2017, 17(8), 1829; https://doi.org/10.3390/s17081829

Achieve Location Privacy-Preserving Range Query in Vehicular Sensing

1
School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798, Singapore
2
Faculty of Computer Science, University of New Brunswick, Fredericton, NB E3B 5A3, Canada
3
School of Computer Science and Information Engineering ,Zhejiang Gongshang University, Hangzhou 310018, China
*
Author to whom correspondence should be addressed.
Received: 12 June 2017 / Revised: 21 July 2017 / Accepted: 2 August 2017 / Published: 8 August 2017
(This article belongs to the Section Sensor Networks)
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Abstract

Modern vehicles are equipped with a plethora of on-board sensors and large on-board storage, which enables them to gather and store various local-relevant data. However, the wide application of vehicular sensing has its own challenges, among which location-privacy preservation and data query accuracy are two critical problems. In this paper, we propose a novel range query scheme, which helps the data requester to accurately retrieve the sensed data from the distributive on-board storage in vehicular ad hoc networks (VANETs) with location privacy preservation. The proposed scheme exploits structured scalars to denote the locations of data requesters and vehicles, and achieves the privacy-preserving location matching with the homomorphic Paillier cryptosystem technique. Detailed security analysis shows that the proposed range query scheme can successfully preserve the location privacy of the involved data requesters and vehicles, and protect the confidentiality of the sensed data. In addition, performance evaluations are conducted to show the efficiency of the proposed scheme, in terms of computation delay and communication overhead. Specifically, the computation delay and communication overhead are not dependent on the length of the scalar, and they are only proportional to the number of vehicles. View Full-Text
Keywords: range query; location privacy preservation; vehicular sensing range query; location privacy preservation; vehicular sensing
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Kong, Q.; Lu, R.; Ma, M.; Bao, H. Achieve Location Privacy-Preserving Range Query in Vehicular Sensing. Sensors 2017, 17, 1829.

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