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ZENODO
Dataset . 2018
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2018
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2018
License: CC BY
Data sources: Datacite
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VeReMi: A Dataset for Comparable Evaluation of Misbehavior Detection in VANETs

Research datakeyboard_double_arrow_right Dataset 29 Dec 2018Embargo end date: 29 Dec 2018 English Publisher:Springer
Authors: van der Heijden, Rens Wouter; Lukaseder, Thomas; Kargl, Frank;

doi: 10.5281/zenodo.20081895 , 10.5281/zenodo.20081894

VeReMi: A Dataset for Comparable Evaluation of Misbehavior Detection in VANETs

Abstract

This is the first, initial version of the Vehicular Reference Misbehavior (VeReMi) dataset, a dataset for the evaluation of misbehavior detection mechanisms for VANETs. 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.

Keywords

misbehavior detection, intrusion detection, vehicular networks

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average