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DenseFlow: Spotting Cryptocurrency Money Laundering in Ethereum Transaction Graphs

Published: 13 May 2024 Publication History

Abstract

In recent years, money laundering crimes on blockchain, especially on Ethereum, have become increasingly rampant, resulting in substantial losses. The unique features of money laundering on Ethereum, such as decentralization and pseudonymity, pose new challenges for Ethereum anti-money laundering. Specifically, the existence of dense and extensive laundering gangs and intricate multilayered laundering pathways makes it exceptionally challenging for regulators to identify suspicious accounts and trace money flows. To address this issue, we propose an innovative DenseFlow framework that effectively identifies and traces money laundering activities by finding dense subgraphs and applying the maximum flow idea. We conduct multiple experiments on four datasets from Ethereum to validate the effectiveness of our approach. The precision of our DenseFlow is 16.34% higher than the start-of-the-art comparison methods on average, highlighting its distinctive contribution to tackling money laundering issues on blockchain.

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  • (2024)Modelling smurfing patterns in cryptocurrencies with integer partitionsIET Blockchain10.1049/blc2.12087Online publication date: 23-Oct-2024

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cover image ACM Conferences
WWW '24: Proceedings of the ACM Web Conference 2024
May 2024
4826 pages
ISBN:9798400701719
DOI:10.1145/3589334
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Published: 13 May 2024

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Author Tags

  1. anti-money laundering
  2. cryptocurrency
  3. ethereum
  4. graph mining
  5. transaction network

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WWW '24
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WWW '24: The ACM Web Conference 2024
May 13 - 17, 2024
Singapore, Singapore

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  • (2024)Modelling smurfing patterns in cryptocurrencies with integer partitionsIET Blockchain10.1049/blc2.12087Online publication date: 23-Oct-2024

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