The significant growth in the use of the Internet and the rapid development of network
technologies are associated with an increased risk of network attacks. Network attacks refer …

Anomaly-based network intrusion detection systems are highly significant in detecting
network attacks. Robust machine learning and deep learning models for identifying network …

Network attacks refer to malicious activities exploiting computer network vulnerabilities to
compromise security, disrupt operations, or gain unauthorized access to sensitive …

With the development of the fifth‐generation networks and artificial intelligence
technologies, new threats and challenges have emerged to wireless communication system …

Rapid developments in network technologies and the amount and scope of data transferred
on networks are increasing day by day. Depending on this situation, the density and …

The rapid advances in the internet and communication fields have resulted in a huge
increase in the network size and the corresponding data. As a result, many novel attacks are …

Network attacks have been around since the beginning of the Internet and they are still
relevant due to the numerous attempts of independent hackers, cybercrime organizations …

In this review, significant literature surveys on machine learning (ML) and deep learning
(DL) techniques for network analysis of intrusion detection are explained. In addition, it …

Deep Learning (DL) provides powerful solutions for detecting network attacks by attempting
to discover patterns of abnormal traffic in the network. Previous studies have demonstrated …

Security analysts and administrators face a lot of challenges to detect and prevent network
intrusions in their organizations, and to prevent network breaches, detecting the breach on …