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VeReMi

Introduced in VeReMi: A Dataset for Comparable Evaluation of Misbehavior Detection in VANETs18 Apr 2018 archive 2025-07-28

The Vehicular Reference Misbehavior (VeReMi) dataset, is a dataset for the evaluation of misbehavior detection mechanisms for VANETs (vehicular networks). This dataset consists of message logs of on-board units, including a labelled ground truth, generated from a simulation environment. The dataset includes malicious messages intended to trigger incorrect application behavior, which is what misbehavior detection mechanisms aim to prevent. The initial dataset contains a number of simple attacks: the idea of this dataset release is not just to provide a baseline for the comparison of detection mechanisms, but also to serve as a starting point for more complex attacks.

Benchmarks archive 2025-07-28

No leaderboard in the archive resolves to this dataset.

Papers archive 2025-07-28

No paper in the archive has a leaderboard row on this dataset; the archive counts 10 papers for it but never published that list.

Dataset loaders archive 2025-07-28

No loader listed in the archive.

Tasks archive 2025-07-28

No task tagged in the archive.

License archive 2025-07-28

No licence recorded in the archive. Absence here is not a statement about the dataset's terms.

Modalities archive 2025-07-28

No modality tagged.

Languages archive 2025-07-28

No language tagged.

Variants archive 2025-07-28

  • VeReMi

1 variant name, as the archive lists them.

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