Print Email Facebook Twitter Dirty Digital Washing Machines Title Dirty Digital Washing Machines: Identifying money laundering in mixing services Author Beudeker, Steffen (TU Delft Technology, Policy and Management) Contributor van Wegberg, R.S. (mentor) Lubbertsen, K.J.M. (graduation committee) Degree granting institution Delft University of Technology Programme Complex Systems Engineering and Management (CoSEM) Date 2022-05-25 Abstract Money laundering has been in existence for a long time, but with recent developments in cryptocurrency technologies, using them as a new method of laundering criminal proceeds has become available to a wider audience of criminals due to mixer services. Bitcoin can be considered pseudonymous, and Mixer services attempt to obfuscate the money trail further by creating transactional chaos. Little is known about the exact functioning of these mixers and how criminals interact with these services. In this thesis, a literature study on existing anti- money laundering (AML) technologies and pattern analysis are applied. Unique to this research is the use of insider mixer administration data combined with the use of public blockchain data. The goal of this research is to gain insight into the degree with which mixer transactions can be identified as money laundering. This will increase the foundation for AML regulation and Law Enforcement procedures. The results show that a small share of the transactions can strongly be identified as money laundering, while for a large share of transactions the identification as money laundering is less strong. In addition, some unexpected phenomena such as reverse money laundering were identified. Subject cybercrimemoney launderingbitcoinmixing services To reference this document use: http://resolver.tudelft.nl/uuid:468da48c-f506-49c8-9668-f95e9e2ab95a Part of collection Student theses Document type master thesis Rights © 2022 Steffen Beudeker Files PDF Final_thesis_s_beudeker.pdf 1.48 MB Close viewer /islandora/object/uuid:468da48c-f506-49c8-9668-f95e9e2ab95a/datastream/OBJ/view