An Anomaly Detection Method for Industrial System Cybersecurity Based on GGL-WAVE-CNN
Abstract Detecting anomalies in industrial system cybersecurity is critical for enabling automated decision-making. Current approaches often struggle to handle complex, unknown topological time series data, thereby necessitating improved anomaly detection accuracy. This paper introduces a novel two-...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Springer
2025-07-01
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| Series: | International Journal of Computational Intelligence Systems |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s44196-025-00832-5 |
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