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

Date

2020-09-25

Advisors

Journal Title

Journal ISSN

ISSN

DOI

Volume Title

Publisher

IEEE

Type

Conference

Peer reviewed

Yes

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

Keywords

Privacy, Internet of Vehicles

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.

Rights

Research Institute

Cyber Technology Institute (CTI)