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Intrusion Detection System for Platooning Connected Autonomous Vehicles
2019
2019 4th South-East Europe Design Automation, Computer Engineering, Computer Networks and Social Media Conference (SEEDA-CECNSM)
The deployment of Connected Autonomous Vehicles (CAVs) in Vehicular Ad Hoc Networks (VANETs) requires secure wireless communication in order to ensure reliable connectivity and safety. However, this wireless communication is vulnerable to a variety of cyber atacks such as spoofing or jamming attacks. In this paper, we describe an Intrusion Detection System (IDS) based on Machine Learning (ML) techniques designed to detect both spoofing and jamming attacks in a CAV environment. The IDS would
doi:10.1109/seeda-cecnsm.2019.8908528
dblp:conf/seeda/KosmanosPAMJBA19
fatcat:pme3pw2i6jc7fbhsdxjjl7alb4