Western-OC2-Lab/MSANA-Online-Data-Stream-Analytics-And-Concept-Drift-Adaptation

Data stream analytics: Implement online learning methods to address concept drift and model drift in dynamic data streams. Code for the paper entitled "A Multi-Stage Automated Online Network Data Stream Analytics Framework for IIoT Systems" published in IEEE Transactions on Industrial Informatics.

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This project helps operations engineers and IT security professionals automatically analyze real-time network traffic and IoT device data. It takes continuous streams of sensor data or network logs as input and outputs optimized insights to detect anomalies or predict events, even when the data patterns change over time. This is for professionals managing Industrial Internet of Things (IIoT) systems or network security.

No commits in the last 6 months.

Use this if you need an automated system to constantly monitor dynamic IIoT network data for issues like intrusions or performance degradation.

Not ideal if your data is static or you only need to analyze historical datasets, as this is specifically designed for real-time, changing data streams.

IIoT network-security operations-monitoring real-time-analytics industrial-automation
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 7 / 25
Maturity 16 / 25
Community 17 / 25

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Stars

34

Forks

8

Language

Jupyter Notebook

License

MIT

Last pushed

Jan 11, 2023

Commits (30d)

0

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