A Rigorous Cross-Dataset Benchmark of Gradient Boosted Decision Trees for Network Intrusion Detection Under Bayesian Hyperparameter Optimisation

Presents a rigorous cross-dataset benchmark of Gradient Boosted Decision Tree models for network intrusion detection, demonstrating the effectiveness of Bayesian hyperparameter optimisation in improving detection performance, robustness, and generalisation across diverse intrusion datasets.