Deep learning (DL), as one of the most active machine learning research fields, has
achieved great success in numerous scientific and technological disciplines, including …

Deep learning (DL) has been widely used in various fields. However, its black-box nature
limits people's understanding and trust in its decision-making process. Therefore, it becomes …

The fact that cloud systems are under the increasing risks of cyber attacks has made the
phenomenon of information security first a need and then a necessity for these systems …

With the continuous occurrence of cybersecurity incidents, network intrusion detection has
become one of the most critical issues in cyber ecosystems. Although previous machine …

Network intrusion detection system plays a critical role in protecting the target network from
attacks. However, most existing detection methods cannot fully utilize the information …

Due to the complexity of the oil and gas station system, the operational data, with various
temporal dependencies and inter-metric dependencies, has the characteristics of diverse …

The analysis of a substantial portion of network data is a requirement for almost any
machine learning-based network intrusion detection method. High dimension features, a …

A persistent, targeted cyber attack is called an advanced persistent threat (APT) attack. The
attack is mainly launched to gain sensitive information, take over the system, and for …

The Distributed Denial of Service (DDoS) attack is considered one of the most critical threats
on the Internet, blocking legitimate users from accessing online services. Botnets have …

As a core tool, anomaly detection based on a generative adversarial network (GAN) is
showing its powerful potential in protecting the safe and stable operation of industrial control …