With the fast-growing network scale, network intrusions are becoming more and more
frequent, volatile and advanced. The problem of how to capture the intrusions in such a …

[Objective] The rapid development of the Internet has brought great convenience to people's
life. However, various malicious network attacks are also increasing, and cyberspace is …

In recent years, the network security situation has become critical. A key component of
network security is intrusion detection. With the continuous development of deep learning …

The use of deep learning models for the network intrusion detection task has been an active
area of research in cybersecurity. Although several excellent surveys cover the growing …

This book presents recent advances in intrusion detection systems (IDSs) using state-of-the-
art deep learning methods. It also provides a systematic overview of classical machine …

Network attack is a significant security issue for modern society. From small mobile devices
to large cloud platforms, almost all computing products, used in our daily life, are networked …

Deep Learning has been very successful in many application domains. However, its
usefulness in the context of network intrusion detection has not been systematically …

Cyber attack is a strong threat to the digital world. So, it's very essential to keep the network
safe. Network Intrusion Detection system is the system to address this problem. Network …

Network intrusion detection systems (IDSs) based on deep learning have reached fairly
accurate attack detection rates. But these deep learning approaches usually have been …

Machine learning and deep learning techniques are widely used to evaluate intrusion
detection systems (IDS) capable of rapidly and automatically recognizing and classifying …