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A Location Privacy Preservation Method Based on Dummy Locations in Internet of Vehicles

Applied sciences, 2021-05, Vol.11 (10), p.4594 [Peer Reviewed Journal]

2021 by the authors. 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 (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2076-3417 ;EISSN: 2076-3417 ;DOI: 10.3390/app11104594

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  • Title:
    A Location Privacy Preservation Method Based on Dummy Locations in Internet of Vehicles
  • Author: Xu, Xianyun ; Chen, Huifang ; Xie, Lei
  • Subjects: Accuracy ; Algorithms ; dummy location ; effective distance ; Entropy ; Internet ; Internet of Vehicles ; Internet of vehicles (IoV) ; Location based services ; location privacy ; location-based services (LBS) ; Methods ; Preservation ; Privacy ; privacy preservation ; Roads & highways ; Semantics ; Site selection ; Third party ; Vehicles ; Wireless networks
  • Is Part Of: Applied sciences, 2021-05, Vol.11 (10), p.4594
  • Description: During the procedure, a location-based service (LBS) query, the real location provided by the vehicle user may results in the disclosure of vehicle location privacy. Moreover, the point of interest retrieval service requires high accuracy of location information. However, some privacy preservation methods based on anonymity or obfuscation will affect the service quality. Hence, we study the location privacy-preserving method based on dummy locations in this paper. We propose a vehicle location privacy-preservation method based on dummy locations under road restriction in Internet of vehicles (IoV). In order to improve the validity of selected dummy locations under road restriction, entropy is used to represent the degree of anonymity, and the effective distance is introduced to represent the characteristics of location distribution. We present a dummy location selection algorithm to maximize the anonymous entropy and the effective distance of candidate location set consisting of vehicle user’s location and dummy locations, which ensures the uncertainty and dispersion of selected dummy locations. The proposed location privacy-preservation method does not need a trustable third-party server, and it protects the location privacy of vehicles as well as guaranteeing the LBS quality. The performance analysis and simulation results show that the proposed location privacy-preservation method can improve the validity of dummy locations and enhance the preservation of location privacy compared with other methods based on dummy locations.
  • Publisher: Basel: MDPI AG
  • Language: English
  • Identifier: ISSN: 2076-3417
    EISSN: 2076-3417
    DOI: 10.3390/app11104594
  • Source: Directory of Open Access Journals
    ROAD: Directory of Open Access Scholarly Resources
    ProQuest Central
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