Özkan Zeybek

Unsupervised deep learning for IoT botnet detection in a surveillance VLAN via multi-source traffic, threat intelligence and honeypot corroboration

An unsupervised deep-learning detection system using autoencoder (AE)-family models that learn normal traffic behaviors and identify anomalies through reconstruction error (MSE) and provides a transparent, reproducible methodology for proactive, scalable, and interpretable botnet detection.