A Safety-Aware Location Privacy-Preserving IoV Scheme with Road Congestion-Estimation in Mobile Edge Computing

Babaghayou, Messaoud; Chaib, Noureddine; Lagraa, Nasreddine; Ferrag, Mohamed Amine; Maglaras, Leandros

Abstract

By leveraging the conventional Vehicular Ad-hoc Networks (VANETs), the Internet of Vehicles (IoV) paradigm has attracted the attention of different research and development bodies. However, IoV deployment is still at stake as many security and privacy issues are looming; location tracking using overheard safety messages is a good example of such issues. In the context of location privacy, many schemes have been deployed to mitigate the adversary’s exploiting abilities. The most appealing schemes are those using the silent period feature, since they provide an acceptable level of privacy. Unfortunately, the cost of silent periods in most schemes is the trade-off between privacy and safety, as these schemes do not consider the timing of silent periods from the perspective of safety. In this paper, and by exploiting the nature of public transport and role vehicles (overseers), we propose a novel location privacy scheme, called OVR, that uses the silent period feature by letting the overseers ensure safety and allowing other vehicles to enter into silence mode, thus enhancing their location privacy. This scheme is inspired by the well-known war strategy “Give up a Pawn to Save a Chariot”. Additionally, the scheme does support road congestion estimation in real time by enabling the estimation locally on their On-Board Units that act as mobile edge servers and deliver these data to a static edge server that is implemented at the cell tower or road-side unit level, which boosts the connectivity and reduces network latencies. When OVR is compared with other schemes in urban and highway models, the overall results show its beneficial use.

Citation

Babaghayou, M., Chaib, N., Lagraa, N., Ferrag, M. A., & Maglaras, L. (2023). A Safety-Aware Location Privacy-Preserving IoV Scheme with Road Congestion-Estimation in Mobile Edge Computing. Sensors, 23(1), Article 531. https://doi.org/10.3390/s23010531

• Journal Article Type: Article
• Acceptance Date: Dec 29, 2022
• Online Publication Date: Jan 3, 2023
• Publication Date: 2023
• Deposit Date: Jan 6, 2023
• Publicly Available Date: Jan 9, 2023
• Journal: Sensors
• Publisher: MDPI
• Peer Reviewed: Peer Reviewed
• Volume: 23
• Issue: 1
• Article Number: 531
• DOI: https://doi.org/10.3390/s23010531
• Keywords: Location tracking, safety and privacy trade-off, road congestion reporting, pseudonym change, location privacy statistics
• Public URL: http://researchrepository.napier.ac.uk/Output/2998018