Fraud Detection in Cryptocurrency Markets with Spatio-Temporal Graph Neural Networks

ArXi:2604.24590v1 Announce Type: new Technological advancements in cryptocurrency markets have increased accessibility for investors, but concurrently exposed them to the risks of market manipulations. Existing fraud detection mechanisms typically rely on machine learning methods that treat each financial asset (i.e., token) and its related transactions independently. However, market manipulation strategies are rarely isolated events, but are rather characterized by coordination, repetition, and frequent transfers among related assets.