SWaT-Anomaly-Detection-Industrial-IoT

This project implements six self-supervised and unsupervised anomaly detection models to identify cyber-attacks in Industrial Control Systems (ICS) using the Secure Water Treatment (SWaT) dataset. The models learn normal system behavior and detect deviations indicative of malicious intrusions targeting sensors and actuators.