Machine Learning based intrusion detection systems for connected autonomous vehicles: A survey

Connected and Autonomous Vehicles (CAVs) expect to dramatically improve road safety and efficiency of the transportation system. However, CAVs can be vulnerable to attacks at different levels, e.g., attacks on intra-vehicle networks and inter-vehicle networks. Those malicious attacks not only result...

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Vydané v:	Peer-to-peer networking and applications Ročník 16; číslo 5; s. 2153 - 2185
Hlavní autori:	Nagarajan, Jay, Mansourian, Pegah, Shahid, Muhammad Anwar, Jaekel, Arunita, Saini, Ikjot, Zhang, Ning, Kneppers, Marc
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York Springer US 01.09.2023 Springer Nature B.V
Predmet:	Autonomous vehicles Communications Engineering Computer Communication Networks Engineering Information Systems and Communication Service Intrusion detection systems Machine learning Networks Signal,Image and Speech Processing Traffic safety Transportation networks Transportation systems Vehicles CAN Bus Machine learning Security threats Intra-vehicle network Inter-vehicle network Intrusion Detection System (IDS) Connected Autonomous Vehicles (CAV)
ISSN:	1936-6442, 1936-6450
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