Intrusion detection systems (IDS) play a crucial role in maintaining network security. With the
increasing sophistication of cyber attack methods, traditional detection approaches are …

Network entities have important asset mapping, vulnerability, and service delivery
applications. In cyberspace, where the network structure is complex and the number of …

With the increasing diversity and complexity of cyber attacks on computer networks, there is
a growing demand for Intrusion Detection Systems (IDS) that can accurately categorize new …

With the advancement of Internet of Things (IoT) technology, IoT systems have been widely
infiltrating and deployed on a large scale globally. Consequently, network attacks on IoT …

With the development of the Internet, the application of computer technology has rapidly
become widespread, driving the progress of Internet of Things (IoT) technology. The attacks …

Now, the Cyber security is facing unprecedented difficulties as a result of the proliferation of
smart devices in the Internet of Things (IoT) environment. The rapid growth in the number of …

Graph neural network-based network intrusion detection systems have recently
demonstrated state-of-the-art performance on benchmark datasets. Nevertheless, these …

Abstract Graph Neural Networks (GNNs) have garnered intensive attention for Network
Intrusion Detection System (NIDS) due to their suitability for representing the network traffic …

The power consumption data from residential households collected by smart meters exhibit
a diverse pattern temporally and among themselves. It is challenging to distinguish between …

Neural network architectures have been used to address multiple real-world problems with
high success. Their extension to graph-structured data started recently to be explored …