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Dataset . 2020
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Data sources: Datacite
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Dataset . 2020
License: CC BY
Data sources: ZENODO
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ZENODO
Dataset . 2020
License: CC BY
Data sources: ZENODO
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ZENODO
Dataset . 2020
License: CC BY
Data sources: Datacite
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IoT-23: A labeled dataset with malicious and benign IoT network traffic

Authors: Garcia, Sebastian; Parmisano, Agustin; Erquiaga, Maria Jose;

IoT-23: A labeled dataset with malicious and benign IoT network traffic

Abstract

IoT-23 is a dataset of network traffic from Internet of Things (IoT) devices. It has 20 malware captures executed in IoT devices, and 3 captures for benign IoT devices traffic. It was first published in January 2020, with captures ranging from 2018 to 2019. These IoT network traffic was captured in the Stratosphere Laboratory, AIC group, FEL, CTU University, Czech Republic. Its goal is to offer a large dataset of real and labeled IoT malware infections and IoT benign traffic for researchers to develop machine learning algorithms. This dataset and its research was funded by Avast Software. The malware was allow to connect to the Internet.

More details here https://www.stratosphereips.org/datasets-iot23

Related Organizations
Keywords

iot, malware, dataset, network traffic, botnet, computer security

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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.
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impulse
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