Interpretable intrusion detection for IoT: a CNN-BiLSTM permutation importance framework for deep feature selection
Industrial intrusion detection systems (IDS) in Industrial Internet of Things (IIoT) environments have to address the problem of handling multi-feature temporally correlated network traffic and dynamic changes in attack patterns. Traditional filter-based feature selection methods, like Mutual Inform...
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| Principais autores: | , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Frontiers Media S.A.
2026-05-01
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| coleção: | Frontiers in Big Data |
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| Acesso em linha: | https://www.frontiersin.org/articles/10.3389/fdata.2026.1813265/full |
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