Enhancing Network Intrusion Detection Performance using Generative Adversarial Networks

arXiv:2404.07464v1 Announce Type: new
Abstract: Network intrusion detection systems (NIDS) play a pivotal role in safeguarding critical digital infrastructures against cyber threats. Machine learning-based detection models applied in NIDS are prevalent today. However, the effectiveness of these machine learning-based models is often limited by the evolving and sophisticated nature of intrusion techniques as well as the lack of diverse and updated training samples. In this research, a novel approach for enhancing the performance of an NIDS through the integration of …

adversarial arxiv critical cs.cr cyber cyber threats detection digital generative generative adversarial networks intrusion intrusion detection machine machine learning nature network network intrusion networks nids performance play prevalent role systems threats today