Kedar Nath Singh

A hybrid CNN-BiLSTM edge-cloud intrusion detection system with online incremental learning and SHAP explainability for smart city IoT

MI-IDS is presented, a hybrid Convolutional Neural Network–Bidirectional Long Short-Term Memory (CNN-BiLSTM) ensemble deployed on a two-tier edge-cloud framework that integrates reservoir-sampling-based incremental learning and SHAP explainability under a single experimentally validated pipeline.