Resampled Intrusion Detection System Datasets for Imbalance Classification

A collection of datasets for Intrusion Detection Systems (IDS) addressing the challenge of class imbalance. The dataset was created by Thi-Thu-Huong and last updated on March 26, 2025. It is hosted on Hugging Face and focuses on applying resampling techniques to improve IDS performance.

Use Cases

• Training intrusion detection models based on resampled network traffic data.
• Benchmarking resampling techniques for class imbalance in security datasets.
• Developing ensemble or cost-sensitive learning methods for IDS based on the provided datasets.

Strengths

• Explicitly addresses the known challenge of class imbalance in IDS datasets.
• Focuses on a practical application of resampling techniques for network security.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count, file formats, and data size are unknown, which may limit suitability assessment.

Provenance

Source

Hugging Face, author Thi-Thu-Huong.

Collection Method

Likely involves applying resampling techniques to existing IDS datasets.

Time Range

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Freshness

Last updated 2025-03-26 07:41:46; freshness should be verified.

Geography

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