Riassunto analitico
The increasing adoption of communication technologies in our society is rapidly growing. One of the most interesting scenarios in which these technologies are gaining high relevance is the transportation system, in which vehicles are shifting from requiring a human driver to the adoption of self-driving solutions and communication technologies to automate their primary task. In particular, the adoption of modern communication technologies to the transportation system enables the development of solutions that involves cooperation between vehicles to reduce commuting time, pollution, and increase road safety. This group of solution is part of the Cooperative Intelligent Transportation System (C-ITS), a term referring to all the solutions designed to increase the efficiency of the transportation system by means of cooperation of intelligent vehicles and infrastructures. One of the key components of C-ITS are the Vehicular ad-Hoc Networks (VANETs), which is the network architecture used by connected vehicles and Road Side Units (RSU) for the definition of Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication systems. In the context of C-ITS there are many different applications of VANETs: from platooning systems, green wave systems, and smart parking areas developed to reduce commuting times and pollution, to solutions targeting the safety of the people inside and around the vehicle, such as the emergency braking system. However, these applications require extensive communication between the involved actors, thus it is necessary to design and implement communication solution that account for modern threats. Current literature already presents solutions designed to ensure reliability of V2X communication systems based on the analysis of the message content to detect anomalies. However, recent works demonstrate that this group of solutions fails in the detection of anomalies specifically designed by considering the vehicular scenario, thus requiring the adoption of more advanced solutions. To this aim, this thesis is focused on the development of a novel cybersecurity solution designed by considering the vehicular scenario, composed by both communication networks and real vehicles. The contributions to the state of the art of this thesis work are the following. At first we improved the state of the art of V2X attacks to demonstrate the poor detection performance of the current reference solution for the cybersecurity of V2X communication. Then, we present a new solution for the detection of targeted attacks to V2X communication, based on the analysis of both communication and data gathered from intelligent vehicles. The results presented in this work demonstrate that by considering the context of intelligent vehicles it is possible to design more performing cybersecurity solutions for future C-ITS applications.
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