Author

A. Najid

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Open access Sep 2026

Fine-Grained IoT Attack Classification Using a Cross-Attention CNN-BiLSTM Model

Deep learning intrusion detection systems perform well when traffic is merely separated into normal and malicious, but fine-grained recognition of the specific attack family remains difficult in Internet of Things (IoT) environments because of severe class imbalance and overlapping feature distributions. This work prop...

Mohamed Fakri, A. Najid, Rachid Ben Said et al. · Future Internet · 0 citations

Open access Sep 2026

A cross-attention CNN–LSTM fusion model for network traffic anomaly detection

Detecting cyber intrusions in modern IoT networks is challenging because of their large scale, heterogeneous device ecosystems, and high-volume traffic patterns. This paper presents a cross-attention CNN–LSTM fusion architecture that jointly learns the spatial and temporal characteristics of network traffic for bin...

Mohamed Fakri, A. Najid, Rachid Ben Said et al. · Scientific Reports · 0 citations