Cross-Domain IoT Anomaly Detection Performance Metrics

Cross-domain detection performance metrics from the WUSTL-IIoT-2021 dataset to the ACI-IoT-2023 dataset. Values are reported as mean ± standard deviation over five independent runs. The dataset was authored by Tiange Yuan and uploaded in April 2026.

Use Cases

• Compare detection performance metrics (mean and standard deviation) across source and target IoT environments.
• Analyze the stability of anomaly detection models via standard deviation values from five runs.
• Benchmark cross-domain transfer learning outcomes between WUSTL-IIoT-2021 and ACI-IoT-2023 datasets.

Strengths

• Performance metrics include standard deviation, indicating result stability.
• Results are derived from five independent runs.
• Data is openly licensed under CC-BY-4.0.

Limitations

• Dataset size is 5.5 KB, indicating a very limited scope of metrics.
• Specific column names and row counts are unknown.
• The dataset contains only aggregated performance scores, not raw detection events.

Provenance

Source

figshare

Collection Method

Cross-domain evaluation results from machine learning experiments.

Freshness

Last updated April 2026.