Industrial IoT Dataset: 500K Synthetic Network Flows

500,000 synthetic network flows generated for Industrial Internet of Things and SCADA systems. The data is intended for anomaly detection and protocol classification tasks. The dataset was sourced from Kaggle, but the author, organization, and last update date are unknown.

Use Cases

• Train anomaly detection models based on synthetic IIoT network flow data.
• Perform protocol classification based on the described network flow characteristics.
• Benchmark machine learning algorithms for cybersecurity in industrial settings.

Strengths

• Contains 500,000 records, providing a substantial volume for model training.
• Synthetic generation likely allows for controlled scenarios and labeled anomalies.

Limitations

• Description metadata is limited; actual data quality requires manual inspection after download.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is known, but other scale details like file size and feature count are unknown.

Provenance

Source

Kaggle

Collection Method

Synthetically generated.