A Hybrid SMOTE-CTGAN and VAE-LSTM Framework for Interpretable Intrusion Detection in Imbalanced Network Traffic
The increasing sophistication of cyber threats and severe class imbalance in network traffic continue to challenge traditional intrusion detection systems. This study proposes a hybrid framework that integrates SMOTE and CTGAN for minority-class augmentation, a Bidirectional Long Short-Term Memory (Bi-LSTM) network for...