Data and code associated with the publication: Improving IDS performance with XGBoost: hyperparameter optimization and real-time analysis

The RS2024 dataset features logs generated by network load balancers (Layer 4) and application load balancers (Layer 7). It includes identified attack traffic through detailed payload analysis, making it ideal for testing Network Intrusion Detection Systems (NIDS) in real-time enterprise scenarios. The GC2024 dataset comprises Zeek network logs, offering a combination of attack traffic and bot traffic sourced from public repositories. This data was obtained from an AWS Elastic Compute Cloud (EC2) instance, presenting a varied setting for assessing security systems. The network intrusion detection model using the eXtreme Gradient Boosting (XGBoost) algorithm was trained on a combined dataset that includes UNSW-NB15, CICIDS2017, TON_IoT, RS-2024, and GC-2024. The model, saved in joblib format, is ready for deployment and can be used for further analysis.