A comprehensive solution for securing connected and autonomous vehicles
Kamal, Mohsin; Kyrkou, Christos; Piperigkos, Nikos; Papandreou, Andreas; Kloukiniotis, Andreas; Casademont Serra, Jordi; Porras, Natalia; Baños, Daniel; Diaz, Rodrigo; Gregorio, Nicola; Hofmann, Klaus Peter; Kapsalas, Petros; Lalos, Aris; Moustakas, Konstantinos; Laoudias, Christos; Theocharides, Theocharides; Ellinas, Georgios
With the advent of Connected and Autonomous Vehicles (CAVs) comes the very real risk that these vehicles will be exposed to cyber-attacks by exploiting various vulnerabilities. This paper gives a technical overview of the H2020 CARAMEL project (currently in the intermediate stage) in which Artificial Intelligent (AI)-based cybersecurity for CAVs is the main goal. Most of the possible scenarios are considered, by which an adversary can generate attacks on CAVs, such as attacks on camera sensors, GPS location, Vehicle to Everything (V2X) message transmission, the vehicle’s On-Board Unit (OBU), etc. The counter-measures to these attacks and vulnerabilities are presented via the current results in the CARAMEL project achieved by implementing the designed security algorithms.
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