CYBER SECURITY MACHINE LEARNING MODEL ASSESSMENT: PERSPECTIVES FROM THE UNSW-NB15 DATASET
Hazem Salim Abdullah; Harith Abdulghani Ibrahim; Mohamed Waleed Jehad; Ahmed khaldoon abdulateef; Muhammed Saleh
Objective: Detection of cyberattacks still remains as one if the challenges. Method: The paper compares the performance of five machine learning classifiers namely Decision Tree (DT), XGBoost (XGB), Gaussian Naive Bayes (GNB), Random Forest (RF) a...