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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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Principais autores: Aparup Roy, Debotosh Bhattacharjee, Ondrej Krejcar
פורמט: Artigo
שפה:Inglês
יצא לאור: Elsevier 2025-06-01
סדרה:Data in Brief
נושאים:
Vehicular reference misbehavior dataset (VeReMi)
Intelligent transportation systems (ITS)
Internet of vehicles (IoV)
Intrusion detection systems (IDS)
Data preprocessing
Dataset optimization
גישה מקוונת:http://www.sciencedirect.com/science/article/pii/S2352340925003312
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