Behavioral mapping of ICS attacks reveals dataset-specific physical patterns and shows binary evaluation metrics substantially overestimate detection performance.
Cy- berattack detection on swat plant industrial control systems using machine learning
2 Pith papers cite this work, alongside 3 external citations. Polarity classification is still indexing.
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Pith papers citing it
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external citations · OpenAlex
years
2026 2verdicts
UNVERDICTED 2representative citing papers
Ti-iLSTM optimizes LSTM for TinyDL to detect logic-layer deception anomalies in PLC-based IWTS, reporting F1=0.983 and AUC=0.998 on SWaT with validation on WADI.
citing papers explorer
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Between Zeros and Ones: Behavioral Characterization Beyond Binary Labeling Across Public ICS Datasets
Behavioral mapping of ICS attacks reveals dataset-specific physical patterns and shows binary evaluation metrics substantially overestimate detection performance.
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Ti-iLSTM: A TinyDL Approach for Logic-Level Anomaly Detection in Industrial Water Treatment Systems
Ti-iLSTM optimizes LSTM for TinyDL to detect logic-layer deception anomalies in PLC-based IWTS, reporting F1=0.983 and AUC=0.998 on SWaT with validation on WADI.