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University of Malaya Malaysia
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Aligning medoid prototypes of ICS traffic enables robust transfer learning for intrusion detection, even when faced with unseen attacks and significant domain shift between industrial plants.
Achieve up to 49% better accuracy in detecting unknown attacks in industrial control systems by cleverly combining transfer learning and clustering to adapt to changing traffic patterns.
