Law enforcement, legal authorities, financial fraud, and financial investigators seek evidence
of financial crimes, and graph technologies provide a unique opportunity to uncover …

This paper analyses a set of simple adaptations that transform standard message-passing
Graph Neural Networks (GNN) into provably powerful directed multigraph neural networks …

The graph isomorphism problem is to determine two finite graphs that are isomorphic which
is not known with a polynomial‐time solution. This paper solves the simple undirected graph …

The original version of this article (doi: 10.1002/cpe. 5484) contains the following errors:• In
the author list,“Ferry Sansoto” should be Ferry Susanto.• To reflect more accurately the …

It has been widely recognized that social network analysis of group relationships and
behaviors come to thrive, so publicity social networks have gained growing attention from …

Money laundering is the process of legitimizing dirty money through complex transactions,
posing a serious threat to a country's financial stability and national security. Nowadays, with …

This thesis examines the effectiveness of Graph Neural Networks (GNNs) in detecting
money laundering activities using transaction data with unreliable labels. It analyses how …

Coronavirus disease 2019 (COVID-19) has gained utmost attention in the current time from
academic research and industrial practices because it continues to rage in many countries …

Structural data have played a prominent role in various domain technologies, such as social
networks, criminal tracking, epidemic spreading, and cheminformatics. Secure multi-party …

Fines and penalties assessed against a bank for failure to comply with regulatory sanctions
result in loss of revenues and reputation. Bank managers who fail to implement effective …