Network Attack Classification Using Random Forest and XGBoost Algorithms on UNSW-NB15 Dataset
The increasing frequency and sophistication of cyber threats have highlighted the need for effective Intrusion Detection Systems (IDS) capable of accurately identifying malicious network traffic. Traditional rule-based frameworks often face limitations in detecting previously unseen attacks and handling high-dimensiona...