Datasets › MTA-KDD'19
MTA-KDD'19 (Malware Traffic Analysis Knowledge Dataset 2019)
Malware Traffic Analysis Knowledge Dataset 2019 (MTA-KDD'19) is an updated and refined dataset specifically tailored to train and evaluate machine learning based malware traffic analysis algorithms. To generate it, that authors started from the largest databases of network traffic captures available online, deriving a dataset with a set of widely-applicable features and then cleaning and preprocessing it to remove noise, handle missing data and keep its size as small as possible. The resulting dataset is not biased by any specific application (although specifically addressed to machine learning algorithms), and the entire process can run automatically to keep it updated.
Source: Letteri et al.
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 1 paper for it but never published that list.
Dataset loaders archive 2025-07-28
1 loader as listed in the archive; links are outbound and not re-checked here.
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
Variants archive 2025-07-28
- MTA-KDD'19
1 variant name, as the archive lists them.
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