Explainable and perturbation-resilient model for cyber-threat detection in industrial control systems Networks
Abstract Deep learning-based intrusion detection systems (DL-IDS) have proven effective in detecting cyber threats. However, their vulnerability to adversarial attacks and environmental noise, particularly in industrial settings, limits practical application. Current IDS models often assume ideal co...
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Main Authors: | Urslla Uchechi Izuazu, Cosmas Ifeanyi Nwakanma, Dong-Seong Kim, Jae Min Lee |
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Format: | Article |
Language: | English |
Published: |
Springer
2025-02-01
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Series: | Discover Internet of Things |
Subjects: | |
Online Access: | https://doi.org/10.1007/s43926-025-00100-0 |
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