Federated Hybrid Deep Learning Framework for IoT Intrusion Detection Using N-BaIoT, CICIoT2023, and BoT-IoT Datasets
This paper presents an end-to-end federated hybrid deep learning framework for IoT intrusion detection that preprocesses and trains diverse models (including CNN, LSTM, and XGBoost) on N-BaIoT, CICIoT2023, and BoT-IoT datasets to achieve strong performance while addressing privacy and resource constraints, with results highlighting the particular challenge of the multiclass CICIoT2023 dataset.
Original paper licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer
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