CARAMEL: results on a secure architecture for connected and autonomous vehicles detecting GPS spoofing attacks

The main goal of the H2020-CARAMEL project is to address the cybersecurity gaps introduced by the new technological domains adopted by modern vehicles applying, among others, advanced Artificial Intelligence and Machine Learning techniques. As a result, CARAMEL enhances the protection against threats related to automated driving, smart charging of Electric Vehicles, and communication among vehicles or between vehicles and the roadside infrastructure. This work focuses on the latter and presents the CARAMEL architecture aiming at assessing the integrity of the information transmitted by vehicles, as well as at improving the security and privacy of communication for connected and autonomous driving. The proposed architecture includes: (1) multi-radio access technology capabilities, with simultaneous 802.11p and LTE-Uu support, enabled by the connectivity infrastructure; (2) a MEC platform, where, among others, algorithms for detecting attacks are implemented; (3) an intelligent On-Board Unit with anti-hacking features inside the vehicle; (4) a Public Key Infrastructure that validates in real-time the integrity of vehicle’s data transmissions. As an indicative application, the interaction between the entities of the CARAMEL architecture is showcased in case of a GPS spoofing attack scenario. Adopted attack detection techniques exploit robust in-vehicle and cooperative approaches that do not rely on encrypted GPS signals, but only on measurements available in the CARAMEL architecture.This work was supported by the European Union’s H2020 research and innovation programme under the CARAMEL project (Grant agreement No. 833611). The work of Christian Vitale, Christos Laoudias and Georgios Ellinas was also supported by the European Union’s Horizon 2020 Research and Innovation Programme under Grant 739551 (KIOS CoE) and from the Republic of Cyprus through the Directorate General for European Programmes, Coordination, and Development. The work of Jordi Casademont and Pouria Sayyad Khodashenas was also supported by FEDER and Secretaria d’Universitats i Recerca del Departament d’Empresa i Coneixement de la Generalitat de Catalunya through projects Fem IoT and SGR 2017-00376 and by the ERDFPeer ReviewedPostprint (author's final draft

The CARAMEL project: a secure architecture for connected and autonomous vehicles

© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.The main goals of the CARAMEL project are to enhance the protection of modern vehicles against cybersecurity threats related to automated driving, smart charging of Electric Vehicles, and communication among vehicles or between vehicles and the roadside infrastructure. This work focuses on the latter and presents the CARAMEL architecture for improving the security and privacy of communication for connected and au- tonomous driving. The proposed architecture includes: (i) multi- radio access technology capabilities, with simultaneous 802.11p and LTE-Uu support; (ii) a MEC platform, where algorithms for detecting attacks are implemented; (iii) an intelligent On- Board Unit with anti-hacking features inside the vehicle; (iv) a Public Key Infrastructure that validates in real-time the integrity of vehicle’s data transmissions. As an indicative application scenario, the interaction between the entities of the CARAMEL architecture is showcased in the case that the GPS locations used by vehicles are spoofed.Peer ReviewedPostprint (published version

A comprehensive solution for securing connected and autonomous vehicles

© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.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.This work was supported by the European Union’s H2020 research and innovation programme under the CARAMEL project (Grant agreement No 833611). The work of M.K., C.K., C.L., T.T., and G.E. has also been supported by the European Union’s Horizon 2020 research and innovation programme under grant agreement No 739551 (KIOS CoE- TEAMING) and from the Republic of Cyprus through the Deputy Ministry of Research, Innovation and Digital Policy. The work of J.C. has also been supported by grants PID2019-106808RA-I00 and PID2020-112675RB funded by MCIN/AEI/10.13039/501100011033.Peer ReviewedPostprint (published version