Anomaly Detection and Machine Learning
Creators
Description
The datasets were preprocessed. Correlated features were removed.
Related papers:
[1] Iman Sharafaldin, Arash Habibi Lashkari, and Ali A. Ghorbani, “Toward Generating a New Intrusion Detection Dataset and Intrusion Traffic Characterization”, 4th International Conference on Information Systems Security and Privacy (ICISSP), Portugal, January 2018
[2] Nour Moustafa, October 16, 2019, "UNSW_NB15 dataset", IEEE Dataport, doi: https://dx.doi.org/10.21227/8vf7-s525.
[3] “Sebastian Garcia, Agustin Parmisano, & Maria Jose Erquiaga. (2020). IoT-23: A labeled dataset with malicious and benign IoT network traffic (Version 1.0.0) [Data set]. Zenodo. http://doi.org/10.5281/zenodo.4743746”
[4] A. D. Kent, “Comprehensive, Multi-Source Cybersecurity Events,” Los Alamos National Laboratory, http://dx.doi.org/10.17021/1179829, 2015.
Files
cic-ids-2017.csv
Files
(729.6 MB)
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md5:9c2d414c28a341bc8a5fbd304787ba62
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542.2 MB | Preview Download |
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md5:ce21be333000a0751d8478d7c0f812d2
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md5:2ef25349346bdcfc1ac9426ce09b695e
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4.6 MB | Preview Download |
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md5:532d91e37d19acd1f9e1f7802231b71b
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94.6 MB | Preview Download |
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md5:08fc6f99cce98d6b9bd968a720b87902
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44.1 MB | Preview Download |
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md5:4ca0121dbb7df72f50e7e275198bbb21
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41.8 MB | Preview Download |