Detecting Roles of Money Laundering in Bitcoin Mixing Transactions: A Goal Modeling and Mining Framework

Abstract

Cryptocurrency has become a new venue for money laundering. Bitcoin mixing services deliberately obfuscate the relationship between senders and recipients, making it difficult to trace suspicious money flow. We believe that the key to demystifying the bitcoin mixing services is to discover agents’ roles in the money laundering process. We propose a goal-oriented approach to modeling, discovering, and analyzing different types of roles in the agent-based business process of the bitcoin mixing scenario using historical bitcoin transaction data. It adopts the agents’ goal perspective to study the roles in the bitcoin money laundering process. Moreover, it provides a foundation to discover real-world agents’ roles in bitcoin money laundering scenarios.