In recent years, graph neural networks (GNNs) have been successfully applied in many
fields due to their characteristics of neighborhood aggregation and have achieved state-of …

With the flourishing of the credit card business and Internet technology, the risk of fraudulent
credit card transactions is ever-increasing due to the complex information involved in the …

With the rapid advancement of 5G technology, the Internet of Things (IoT) has entered a new
phase of application and is rapidly becoming a significant force in promoting economic …

Due to the wide application of dynamic graph anomaly detection in cybersecurity, social
networks, e-commerce, etc., research in this area has received increasing attention. Graph …

The convergence of Blockchain technology and Artificial Intelligence (AI) is exerting a
transformative influence, ushering in a new epoch of security and transparency within the …

In recent years, heterogeneous graph neural networks have been applied to the analysis of
complex networks, and in ethereum transaction, fraudsters disguise themselves as normal …

Mobile crowd sensing (MCS) is an emerging approach to collect data using smart devices.
In MCS, task assignment is described as assigning existing tasks to known workers outside …

Traditional consumer fraud detection usually relies on the relevant regulatory authorities to
conduct inspections through sampling. This would be labor-intensive and inefficient. To …

The development of the Industrial Internet of Things (IIoT) in recent years has resulted in an
increase in the amount of data generated by connected devices, creating new opportunities …

With Ethereum blockchain advancement, the Ethereum platform gathers numerous users. In
this context, traditional phishing appears new fraud methods, resulting in significant losses …