Achieve Location Privacy-Preserving Range Query in Vehicular Sensing
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 accurac...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2018
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/86826 http://hdl.handle.net/10220/44296 |
| _version_ | 1826112695200382976 |
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| author | Kong, Qinglei Lu, Rongxing Ma, Maode Bao, Haiyong |
| author2 | School of Electrical and Electronic Engineering |
| author_facet | School of Electrical and Electronic Engineering Kong, Qinglei Lu, Rongxing Ma, Maode Bao, Haiyong |
| author_sort | Kong, Qinglei |
| collection | NTU |
| description | 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. |
| first_indexed | 2024-10-01T03:11:09Z |
| format | Journal Article |
| id | ntu-10356/86826 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T03:11:09Z |
| publishDate | 2018 |
| record_format | dspace |
| spelling | ntu-10356/868262020-03-07T13:57:30Z Achieve Location Privacy-Preserving Range Query in Vehicular Sensing Kong, Qinglei Lu, Rongxing Ma, Maode Bao, Haiyong School of Electrical and Electronic Engineering Range Query Location Privacy Preservation 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. Published version 2018-01-10T04:04:13Z 2019-12-06T16:29:44Z 2018-01-10T04:04:13Z 2019-12-06T16:29:44Z 2017 Journal Article Kong, Q., Lu, R., Ma, M., & Bao, H. (2017). Achieve Location Privacy-Preserving Range Query in Vehicular Sensing. Sensors, 17(8), 1829-. 1424-8220 https://hdl.handle.net/10356/86826 http://hdl.handle.net/10220/44296 10.3390/s17081829 en Sensors © 2017 by The Author(s). Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). 16 p. application/pdf |
| spellingShingle | Range Query Location Privacy Preservation Kong, Qinglei Lu, Rongxing Ma, Maode Bao, Haiyong Achieve Location Privacy-Preserving Range Query in Vehicular Sensing |
| title | Achieve Location Privacy-Preserving Range Query in Vehicular Sensing |
| title_full | Achieve Location Privacy-Preserving Range Query in Vehicular Sensing |
| title_fullStr | Achieve Location Privacy-Preserving Range Query in Vehicular Sensing |
| title_full_unstemmed | Achieve Location Privacy-Preserving Range Query in Vehicular Sensing |
| title_short | Achieve Location Privacy-Preserving Range Query in Vehicular Sensing |
| title_sort | achieve location privacy preserving range query in vehicular sensing |
| topic | Range Query Location Privacy Preservation |
| url | https://hdl.handle.net/10356/86826 http://hdl.handle.net/10220/44296 |
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