Enhancing V2X Security Through Combined Rule-Based and DL-Based Local Misbehavior Detection in Roadside Units

In this paper, we address the limitations of existing deep learning (DL) methods for local misbehavior detection (LMBD) in vehicle-to-everything (V2X) communication systems by proposing an approach that combines rule-based and DL-based techniques. Conventional DL-based methods at roadside units (RSU...

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Detalhes bibliográficos

Principais autores:	Seungyoung Park, Duksoo Kim, Seokwoo Lee
Formato:	Artigo
Idioma:	Inglês
Publicado em:	IEEE 2024-01-01
Colecção:	IEEE Open Journal of Intelligent Transportation Systems
Assuntos:	Vehicle-to-everything (V2X) misbehavior detection (MBD) roadside unit (RSU) misbehavior report (MBR) multi-access edge computing (MEC) deep learning
Acesso em linha:	https://ieeexplore.ieee.org/document/10715733/
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