Attention-augmented CNN-BiLSTM with temporal-spatial attention for imbalanced multi-class network intrusion detection
The proposed Attention-Augmented CNN-BiLSTM architecture incorporating a lightweight Temporal-Spatial Attention Module (TSAM) achieves an effective balance between computational efficiency, robustness to severe class imbalance, and accurate multi-class intrusion detection for next-generation IoT security systems.