A deep learning-based IDS for IoT: model proposal and comparative study of dataset balancing techniques
Intrusion detection in Internet of Things (IoT) environments presents challenges due to the diversity of connected devices and their resource limitations. IoT networks generate complex, imbalanced traffic where benign activity predominates over attack instances. This imbalance hampers the performanc...
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| Huvudupphov: | , , , |
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| Materialtyp: | Artigo |
| Språk: | Inglês |
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Taylor & Francis Group
2026-03-01
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| Serie: | Journal of Information and Telecommunication |
| Ämnen: | |
| Länkar: | https://www.tandfonline.com/doi/10.1080/24751839.2026.2640249 |
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