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Detecting potential money laundering addresses in the Bitcoin blockchain using unsupervised machine learning

Detecting potential money laundering addresses in the Bitcoin blockchain using unsupervised machine learning
Detecting potential money laundering addresses in the Bitcoin blockchain using unsupervised machine learning

Money laundering is a serious problem worldwide, especially in the crypto market. This is mostly because of the anonymity that many cryptocurrencies offer. That is one of the reasons why cryptocurrencies are a haven for money laundering, because it is easier for criminal entities to buy the currency and then trade it for real fiat money. Detecting money laundering in cryptocurrency can be tricky because the crypto network is large and convoluted and nearly impossible to analyze by hand. What we can do is look at addresses that took part in transactions as actors and then use machine learning to predict what addresses are possibly laundering money. In this paper we intend to analyze methods that can be used to detect money laundering in Bitcoin using machine learning to empower investigators to more accurately and efficiently determine whether a suspicious activity is money laundering.

1530-1605
1562-1571
IEEE Computer Society
Stefánsson, Hilmar Páll
985fef2d-34a9-4519-9601-20fb2b1a9a18
Grímsson, Huginn Sær
0cf9d49f-e6ab-4bcc-9528-5084c0add047
Pórðarson, Jón Kristinn
44448246-9167-4303-ad0e-08fc0b2629e6
Óskarsdóttir, María
d159ed8f-9dd3-4ff3-8b00-d43579ab71be
Bui, Tung X.
Stefánsson, Hilmar Páll
985fef2d-34a9-4519-9601-20fb2b1a9a18
Grímsson, Huginn Sær
0cf9d49f-e6ab-4bcc-9528-5084c0add047
Pórðarson, Jón Kristinn
44448246-9167-4303-ad0e-08fc0b2629e6
Óskarsdóttir, María
d159ed8f-9dd3-4ff3-8b00-d43579ab71be
Bui, Tung X.

Stefánsson, Hilmar Páll, Grímsson, Huginn Sær, Pórðarson, Jón Kristinn and Óskarsdóttir, María (2022) Detecting potential money laundering addresses in the Bitcoin blockchain using unsupervised machine learning. Bui, Tung X. (ed.) In Proceedings of the 55th Annual Hawaii International Conference on System Sciences, HICSS 2022. vol. 2022-January, IEEE Computer Society. pp. 1562-1571 .

Record type: Conference or Workshop Item (Paper)

Abstract

Money laundering is a serious problem worldwide, especially in the crypto market. This is mostly because of the anonymity that many cryptocurrencies offer. That is one of the reasons why cryptocurrencies are a haven for money laundering, because it is easier for criminal entities to buy the currency and then trade it for real fiat money. Detecting money laundering in cryptocurrency can be tricky because the crypto network is large and convoluted and nearly impossible to analyze by hand. What we can do is look at addresses that took part in transactions as actors and then use machine learning to predict what addresses are possibly laundering money. In this paper we intend to analyze methods that can be used to detect money laundering in Bitcoin using machine learning to empower investigators to more accurately and efficiently determine whether a suspicious activity is money laundering.

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More information

Published date: 2022
Additional Information: Publisher Copyright: © 2022 IEEE Computer Society. All rights reserved.
Venue - Dates: 55th Annual Hawaii International Conference on System Sciences, HICSS 2022, , Virtual, Online, 2022-01-03 - 2022-01-07

Identifiers

Local EPrints ID: 507836
URI: http://eprints.soton.ac.uk/id/eprint/507836
ISSN: 1530-1605
PURE UUID: 31f8817c-797b-4cf2-a444-05e4930a2b15
ORCID for María Óskarsdóttir: ORCID iD orcid.org/0000-0001-5095-5356

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Date deposited: 06 Jan 2026 18:03
Last modified: 08 Jan 2026 03:27

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Contributors

Author: Hilmar Páll Stefánsson
Author: Huginn Sær Grímsson
Author: Jón Kristinn Pórðarson
Author: María Óskarsdóttir ORCID iD
Editor: Tung X. Bui

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