IDS IoT Dataset: Network Traffic for Intrusion Detection

An IoT network traffic dataset intended for intrusion detection system development. The dataset is hosted on Kaggle and is described as suitable for classification tasks. Specific details on size, origin, and temporal coverage are not provided in the available metadata.

Use Cases

• Train binary classifiers to detect malicious versus benign network traffic.
• Develop multiclass classifiers to identify specific types of network intrusions.
• Benchmark machine learning models for IoT network security applications.

Strengths

• Dataset is explicitly designed for intrusion detection, providing a clear application focus.
• Platform tags indicate suitability for both binary and multiclass classification tasks.

Limitations

• Row count, file size, and column-level documentation are absent; data structure must be inspected after download.
• Author, organization, and license information are unknown, which may affect usage rights and credibility assessment.
• Last update date is unknown; freshness unverified.

Provenance

Source

Kaggle

Collection Method

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Time Range

null

Freshness

null

Geography

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