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The overwhelming majority of ICS cybersecurity datasets ignore critical early-stage threats, limiting the effectiveness of intrusion detection research.
Temporal inconsistencies in Digital Twins can serve as powerful indicators of cyber physical attacks, achieving up to 98% detection reliability without needing labeled attack data.
Conventional binary metrics can mask critical performance insights, with macro F1 scores plummeting from 85.44% to 37.84% when using behavior-proxy multiclass predictions.
