Inside the Crypto Laundering Machine: A Taxonomic Study of Crypto Money Laundering Schemes and Countermeasures

In plain words

Criminals who steal or extort cryptocurrency still have to turn it into money they can spend without being traced. This thesis maps how they do that. It reviews academic papers, regulator reports, and industry investigations, then organises the laundering methods into a taxonomy: the broad strategies (hiding the trail of a transaction, mixing funds with other people's, hopping between blockchains, and so on) and the services and tools used to carry them out, from mixers and bridges to NFT marketplaces and gambling sites. It then looks at what works against them, both detecting laundering after the fact and making it harder in the first place, and lists the problems that remain open for researchers, regulators, and exchanges.

Abstract

The rise of Web3 and Decentralized Finance (DeFi) has enabled borderless access to financial services built on smart contracts and blockchains. The same trustless, permissionless nature creates fertile ground for financial crime, and money laundering in particular, since it lets proceeds from scams, exploits, and market manipulation move covertly. Prior work on crypto money laundering is fragmented, dated, or limited to single vectors. This thesis addresses that through a systematic, interdisciplinary review of academic, regulatory, and industry sources. It consolidates known schemes into a taxonomy of money laundering in Web3, organised into high-level obfuscation strategies and the intermediary mechanisms that realise them, and identifies emerging schemes not previously documented. It then surveys countermeasures across detection and prevention as pursued in academia, regulation, and industry, and draws out the open challenges and future directions toward a more transparent Web3 financial ecosystem.

Defence slides

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