An intrusion detection system (IDS) is an important protection instrument for detecting
complex network attacks. Various machine learning (ML) or deep learning (DL) algorithms …

Nowadays, distributed data processing in cloud computing has gained increasing attention
from many researchers. The intense transfer of data has made the network an attractive and …

Pervasive growth and usage of the Internet and mobile applications have expanded
cyberspace. The cyberspace has become more vulnerable to automated and prolonged …

Network intrusion detection systems play an important role in protecting the network from
attacks. However, Existing network intrusion data is imbalanced, which makes it difficult to …

The network intrusion detection system is an important tool for protecting computer networks
against threats and malicious attacks. Many techniques have recently been proposed; …

The high dimension, complexity, and imbalance of network data are hot issues in the field of
intrusion detection. Nowadays, intrusion detection systems face some challenges in …

To explore the advantages of adversarial learning and deep learning, we propose a novel
network intrusion detection model called SAVAER-DNN, which can not only detect known …

In this work, we apply a two stage anomaly-based network intrusion detection process using
the UNSW-NB15 dataset. We use Recursive Feature Elimination and Random Forests …

Due to the growth of internet security issues, Network Intrusion Detection System (NIDS)
becomes an integral part of the IoT environment. In the past, most research on intrusion …

With an increasing number of services connected to the internet, including cloud computing
and Internet of Things (IoT) systems, the prevention of cyberattacks has become more …