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# Dynamic-time-warping-based-anomaly-detection-for-industrial-control-system | ||
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This repository presents a comprehensive approach to anomaly detection in Industrial Control Systems (ICS), with a focus on the Secure Water Treatment DataSet (SWaT). The implementation incorporates cutting-edge machine learning techniques, including Isolation Forest and Autoencoder models, augmented by the powerful Dynamic Time Warping (DTW) algorithm. | ||
This repository presents a comprehensive approach to anomaly detection in **Industrial Control Systems (ICS)**, with a focus on the **Secure Water Treatment DataSet (SWaT)**. | ||
The implementation incorporates cutting-edge machine learning techniques, including **Isolation Forest** and **Autoencoder** models, augmented by the powerful **Dynamic Time Warping (DTW) algorithm**. |