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 . 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.
Email Address of Submitting Authoradam.email@example.com
ORCID of Submitting Author0000-0002-3261-0634
Submitting Author's InstitutionMacquarie University
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