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 …

The escalating threat of phishing attacks poses significant challenges to cybersecurity,
necessitating innovative approaches for detection and mitigation. This paper addresses this …

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 applications and is rapidly becoming a significant force in promoting economic …

Abstract Graph Neural Networks (GNNs) have emerged as a powerful tool for analyzing and
modeling graph-structured data. In recent years, GNNs have gained significant attention in …

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 …

Blockchain technology offers significant potential for enhancing efficiency in logistics
operations by providing a decentralized and immutable ledger for tracking goods. This …

As the popularity of cryptocurrencies grows, the threat of phishing scams on trading
networks is growing. Detecting unusual transactions within the complex structure of these …