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Classifying ransomware-Bitcoin nodes using graph embeddings
  • Adam Turner ,
  • Muhammad Ikram ,
  • Allon J. Uhlmann
Adam Turner
Macquarie University

Corresponding Author:[email protected]

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Muhammad Ikram
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Allon J. Uhlmann
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Abstract

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.