The Impact of the Adversary's Eavesdropping Stations on the Location Privacy Level in Internet of Vehicles

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Date
2020-09-25Author
Abstract
The Internet of Vehicles (IoV) has got the interest of different research bodies as a promising technology. IoV is
mainly developed to reduce the number of crashes by enabling vehicles to sense the environment and spread their locations
to the neighborhood via safety-beacons to enhance the system functioning. Nevertheless, a bunch of security and privacy threats
is looming; by exploiting the spatio-data included in these beacons. A lot of privacy schemes were developed to cope with
the problem like CAPS, CPN, RSP, and SLOW. The schemes provide a certain level of location privacy yet the strength of
the adversary, e.g., the number of eavesdropping stations has not been fully considered. In this paper, we aim at investigating
the effect of the adversary’s eavesdropping stations number and position on the overall system functioning via privacy and QoS
metrics. We also show the performances of these schemes in a manhattan-grid model which gives a comparison between the
used schemes. The results show that both the number and the emplacement of the eavesdropping stations have a real negative
impact on the achieved location privacy of the IoV users.
Description
Citation : Babaghayou, M., Labraoui, N., Adamou, A., Ferrag, A., Maglaras, L. (2020) The Impact of the Adversary's Eavesdropping Stations on the Location Privacy Level in Internet of Vehicles. 5th IEEE South-East Europe Design Automation, Computer Engineering, Computer Networks and Social Media Conference (SEEDA-CECNSM 2020), Corfu, Greece, September 2020.
Research Institute : Cyber Technology Institute (CTI)
Peer Reviewed : Yes