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Novel Centralized Pseudonym Changing Scheme for Location Privacy in V2X Communication

Author

Listed:
  • Ahmed Didouh

    (IEMN DOAE, UMR CNRS 8520, Polytechnic University Hauts-de-France, 59300 Valenciennes, France)

  • Yassin El Hillali

    (IEMN DOAE, UMR CNRS 8520, Polytechnic University Hauts-de-France, 59300 Valenciennes, France)

  • Atika Rivenq

    (IEMN DOAE, UMR CNRS 8520, Polytechnic University Hauts-de-France, 59300 Valenciennes, France)

  • Houda Labiod

    (INFRES Computing and Networks ENST, Telecom, 91120 Paris, France)

Abstract

Vehicular ad hoc networks allow vehicles to share their information for the safety and efficiency of traffic purposes. However, information sharing can threaten the driver’s privacy as it includes spatiotemporal information, and the messages are unencrypted and broadcasted periodically. Therefore, they cannot estimate their privacy level because it also depends on their surroundings. This article proposes a centralized adaptive pseudonym change scheme that permits the certificate’s authority to adjust the pseudonyms assignment for each requesting vehicle. This scheme adapts dynamically depending on the density of the traffic environment and the user’s privacy level, and it aims to solve the trade-off problem between wasting pseudonyms and Sybil attack. We employ a Knapsack problem-based algorithm for target tracking and an entropy-based method to measure each vehicle’s privacy. In order to demonstrate the applicability of our framework, we use real-life data captured during the interoperability tests of the European project InterCor. According to the experimental results, the proposed scheme could easily estimate the level of confidentiality and, therefore, may best respond to the adaptation of the pseudonyms.

Suggested Citation

  • Ahmed Didouh & Yassin El Hillali & Atika Rivenq & Houda Labiod, 2022. "Novel Centralized Pseudonym Changing Scheme for Location Privacy in V2X Communication," Energies, MDPI, vol. 15(3), pages 1-18, January.
  • Handle: RePEc:gam:jeners:v:15:y:2022:i:3:p:692-:d:727570
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