Detection of Money Laundering Address over the Ethereum Blockchain

Abstract

The increasing prevalence of Ethereum has led to a growing occurrence of illegal activities, including money laundering, the need to effectively detect money laundering transactions on the Ethereum platform has become crucial. However, there is currently limited research on detecting money laundering addresses within Ethereum. In this paper, we address this gap by proposing the use of heuristic algorithms to to solve the money laundering problem with a special focus on address detection. In this work, we collected nearly 7000,000 transaction records from Ethereum and introduced a heuristic algorithm based on cyclic transaction patterns to identify money laundering addresses primarily associated with such patterns. Our proposed algorithm analyzes transaction patterns and strategies in historical money laundering transaction data, providing valuable insights and revealing the behaviors and psychological changes of money launderers.