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Processed IDS Datasets for Reproducible Multiclass Active Learning Experiments

This repository provides processed versions of publicly available intrusion detection datasets prepared for reproducible experiments in multiclass and imbalanced Active Learning scenarios. The datasets follow a standardized preprocessing and partitioning pipeline, as described in the paper &l

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CreatorARRUDA, RODOLFO AUGUSTO DA
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Published2026-01-31
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DOI10.5281/zenodo.18443124
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Downloads14
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Licensecc-by-4.0
File Size1.5 GB
Data TypeDataset
Published2026
Licensecc-by-4.0
Total Views38
Total Downloads14

This repository provides processed versions of publicly available intrusion detection datasets prepared for reproducible experiments in multiclass and imbalanced Active Learning scenarios. The datasets follow a standardized preprocessing and partitioning pipeline, as described in the paper “Active Learning for Multiclass Imbalanced Intrusion Detection: Multi-Dataset Evaluation”. All data preprocessing and dataset treatment procedures are publicly available at https://github.com/rodolfoarruda/share/tree/main/datasets_treatment. The original datasets are properly cited in the associated publication and remain available from their official sources.

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Processed IDS Datasets for Reproducible Multiclass Active Learning… (Full Dataset)1.5 GB
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ReadmeVia DOI record
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Files are hosted on the source repository. Click download to access the full dataset.

ARRUDA, RODOLFO AUGUSTO DA (2026). Processed IDS Datasets for Reproducible Multiclass Active Learning Experiments. https://doi.org/10.5281/zenodo.18443124