Medoid prototype alignment detects unknown attacks across industrial plants by aligning domain-specific medoid summaries rather than raw samples, yielding 0.843 average accuracy on gas and water system transfers.
Organ-agents: Virtual human physiology simulator via llms
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 2verdicts
UNVERDICTED 2representative citing papers
A domain adaptation framework with spectral feature alignment and K-Medoids clustering after PCA improves unknown attack detection accuracy by up to 49% over baselines and gains another 26% from the clustering step in cross-domain ICS intrusion detection.
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Medoid Prototype Alignment for Cross-Plant Unknown Attack Detection in Industrial Control Systems
Medoid prototype alignment detects unknown attacks across industrial plants by aligning domain-specific medoid summaries rather than raw samples, yielding 0.843 average accuracy on gas and water system transfers.
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Clustering-Enhanced Domain Adaptation for Cross-Domain Intrusion Detection in Industrial Control Systems
A domain adaptation framework with spectral feature alignment and K-Medoids clustering after PCA improves unknown attack detection accuracy by up to 49% over baselines and gains another 26% from the clustering step in cross-domain ICS intrusion detection.