Network Intrusion Detection Based on Conditional Wasserstein Generative Adversarial Network and Cost-Sensitive Stacked Autoencoder

In the field of intrusion detection, there is often a problem of data imbalance, and more and more unknown types of attacks make detection difficult. To resolve above issues, this article proposes a network intrusion detection model called CWGAN-CSSAE, which combines improved conditional Wasserstein...

Бүрэн тодорхойлолт

Номзүйн дэлгэрэнгүй

Үндсэн зохиолчид:	Guoling Zhang, Xiaodan Wang, Rui Li, Yafei Song, Jiaxing He, Jie Lai
Формат:	Artigo
Хэл сонгох:	Inglês
Хэвлэсэн:	IEEE 2020-01-01
Цуврал:	IEEE Access
Нөхцлүүд:	Intrusion detection conditional Wasserstein GAN stacked autoencoder imbalanced classification cost-sensitive regularization
Онлайн хандалт:	https://ieeexplore.ieee.org/document/9229088/
Шошгууд:	Шошго нэмэх Шошго байхгүй, Энэхүү баримтыг шошголох эхний хүн болох!