NIDS-28: Multi-Class Network Intrusion Detection Dataset

NIDS-28 is a multi-class network intrusion detection dataset. The dataset's author, organization, size, and temporal coverage are not specified in the available metadata. It was sourced from the Kaggle platform.

Use Cases

• Train multi-class classifiers to identify different types of network attacks based on network traffic features.
• Benchmark the performance of anomaly detection algorithms against labeled intrusion data.
• Research network traffic patterns associated with malicious activity.

Strengths

• Dataset is explicitly designed for multi-class classification, a common and practical task in network security.
• The title clearly indicates its primary application for Network Intrusion Detection Systems (NIDS).

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

Kaggle

Collection Method

Method of data gathering is not described.

Time Range

Temporal coverage is unknown.

Freshness

Last update date is unknown; freshness unverified.

Geography

Spatial coverage is unknown.