Privacy Preservation in Vehicular Ad Hoc Networks

Abstract

Intelligent Transport Systems (ITSs) provide to the public sphere safe and comfortable journeys. Their advent is reflected in the mobilization of governments, car manufacturers, researchers and digital giants. Inter-vehicular communications are today considered to be the most important element in ITSs. In fact, they permit to increase the road safety and enhance the comfort of drivers and passengers. These communications constitute a network called Vehicular Ad Hoc Network (VANET). Most of the applications developed in the field of VANETs are based on the periodic exchange of beacon messages that contain personal information about their sender such as the location of the vehicle. However, this information can be intercepted and collected by an adversary to identify and track vehicles. This attack allows the adversary to draw the paths of the drivers, and thus know their activities. As a result, this attack leads to threats on the user’s location privacy in vehicular networks. Hence, the security of this data in vehicular networks is a challenge for researchers. In this context, the pseudonym change approach is widely accepted as a solution to protect the privacy of users in VANETs. Different pseudonym-based schemes and protocols for the protection of privacy have been proposed in the literature. In this thesis, we are interested in preserving the privacy of users in VANETs. In the first part of this thesis, we introduce the state of the art of VANETs and their security as well as privacy protection schemes. In the second part, we look for how to generate pseudonyms, and introduce an effective Pseudonyms Generation Protocol (PGP), in order to support the conditional tracking, and thus to achieve the requirement of conditional privacy preservation. Finally, we present the Context-based Location Privacy Scheme (CLPS) for the preservation of users’ privacy in VANETs. The first contribution of CLPS is a Context-based Pseudonym Changing Strategy (CPCS), which is characterized by a prevention against the linkability of pseudonyms while taking into account the characteristics of the VANET (high mobility, density, etc.). The second contribution of CLPS is the elaboration of an adversary model, called cheating attack that can be applied against the proposed pseudonym changing strategy CPCS. Then, a Context-based Cheating Detection Mechanism (CCDM) is developed in order to confront this attack.