Improving internet of vehicles research: A systematic preprocessing framework for the VeReMi datasetZenodo

The Vehicular Reference Misbehavior Dataset (VeReMi) is a vital resource for advancing Intelligent Transportation Systems (ITS) and the Internet of Vehicles (IoV). However, its large size (∼7 GB) and inherent class imbalance pose significant challenges for machine learning model development. This pa...

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Auteurs principaux:	Aparup Roy, Debotosh Bhattacharjee, Ondrej Krejcar
Format:	Artigo
Langue:	Inglês
Publié:	Elsevier 2025-06-01
Collection:	Data in Brief
Sujets:	Vehicular reference misbehavior dataset (VeReMi) Intelligent transportation systems (ITS) Internet of vehicles (IoV) Intrusion detection systems (IDS) Data preprocessing Dataset optimization
Accès en ligne:	http://www.sciencedirect.com/science/article/pii/S2352340925003312
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