Classifying ransomware-Bitcoin nodes using graph embeddings

This research develops a methodology to identify transactions through data-driven tracking and analysis of ransomware-Bitcoin payment networks [30]. We demonstrate the methodology by applying the GraphSAGE embedding algorithm to the WannaCry ransomware-Bitcoin cash-out network. The paper takes a data-driven approach to building a machine learning system that allows analysts to define features relevant to ransomware-Bitcoin payment networks.