A Detailed Analysis of the Multi-Class Classification Problem in Network Intrusion Detection using Resampling Techniques

Abstract

Cybersecurity has recently become a significant concern. In particular, machine learning algorithms are known to help identify cyberattacks such as network intrusion.However, common network intrusion datasets are often imbalanced: the normal traffic behaviors constitute the majority of the dataset, while intrusion traffic behaviors form a significantly smaller portion. We conduct a detailed analysis on the impact of SVM Support Vector Machine WGAN-GP Wasserstein GAN with Gradient Penalty xv