Cyber-attacks pose increasing challenges in precisely detecting intrusions, risking data
confidentiality, integrity, and availability. This review paper presents recent IDS taxonomy, a …

Publicly available datasets are an indispensable tool for researchers, as they allow testing
new algorithms on a wide range of different scenarios and making scientific experiments …

The frequency of cyber-attacks on the Internet of Things (IoT) networks has significantly
increased in recent years. Anomaly-based network intrusion detection systems (NIDSs) offer …

Intrusion detection is a critical aspect of network security to protect computer systems from
unauthorized access and attacks. The capacity of traditional intrusion detection systems …

This paper investigates graph neural networks (GNNs) applied for self-supervised intrusion
and anomaly detection in computer networks. GNNs are a deep learning approach for graph …

Cyberattacks represent an ever-growing threat that has become a real priority for most
organizations. Attackers use sophisticated attack scenarios to deceive defense systems in …

In recent years, many methods for intrusion detection systems (IDS) have been designed
and developed in the research community, which have achieved a perfect detection rate …

Healthcare is one of the key areas of prospect for the Internet of Things (IoT). To facilitate
better medical services, enormous growth in the field of the Internet of Medical Things (IoMT) …

Computer viruses, malicious, and other hostile attacks can affect a computer network.
Intrusion detection is a key component of network security as an active defence technology …

Industrial Internet of Things (IIoT) represents the expansion of the Internet of Things (IoT) in
industrial sectors. It is designed to implicate embedded technologies in manufacturing fields …