Network Traffic Anomaly Detection for Server Security Using a Hybrid CNN–BiLSTM and LightGBM Optimized by Whale Optimization Algorithm
A hybrid anomaly detection pipeline that combines deep learning for representation learning with gradient-boosted decision trees for multiclass classification on structured traffic features is proposed, designed with practical deployment in mind by leveraging a tree-based classifier on learned features.