Nowadays, many vehicles are connected to the Internet for providing enhanced or additional functionalities to drivers. However, the existing vehicle communication protocols are not designed for cybersecurity. As a result, Autonomous Vehicles (AVs) are exposed to hacker attacks which could jeopardize the safety of passengers. In this paper, a novel Informative Model Predictive Scheme (I-MPS) against Replay Attacks (RAs) and Denial of Service (DoS) attacks for AVs is proposed. The effectiveness of the scheme is shown by numerical simulations of an autonomous vehicles during an overtaking and is compared against a typical architecture not implementing the I-MPS.
A Model Predictive Scheme for Autonomous Vehicles Cybersecurity / Terlizzi, M.; Mariani, V.; Glielmo, L.. - 2021-:(2021), pp. 66-71. (Intervento presentato al convegno 5th International Conference on Control and Fault-Tolerant Systems, SysTol 2021 tenutosi a fra nel 2021) [10.1109/SysTol52990.2021.9595697].
A Model Predictive Scheme for Autonomous Vehicles Cybersecurity
Glielmo L.
2021
Abstract
Nowadays, many vehicles are connected to the Internet for providing enhanced or additional functionalities to drivers. However, the existing vehicle communication protocols are not designed for cybersecurity. As a result, Autonomous Vehicles (AVs) are exposed to hacker attacks which could jeopardize the safety of passengers. In this paper, a novel Informative Model Predictive Scheme (I-MPS) against Replay Attacks (RAs) and Denial of Service (DoS) attacks for AVs is proposed. The effectiveness of the scheme is shown by numerical simulations of an autonomous vehicles during an overtaking and is compared against a typical architecture not implementing the I-MPS.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
