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Cryptocurrencies are increasingly viewed as a significant tool for money laundering due to their pseudonymous nature, decentralized structure, and the ease with which they enable cross-border fund transfers. However, despite growing concerns, empirical research on how cryptocurrencies facilitate illicit activities remains limited. To address this gap, we analyzed over 1,500 posts from a Darkweb community with more than 40,000 members, specifically focused on money laundering, using natural language processing (NLP) techniques. Our findings reveal key trends, methods, and strategies discussed by community members to launder illicit proceeds and evade detection. More importantly, the study highlights the challenges these activities present to existing regulatory frameworks, illustrating how money launderers exploit gaps in policy. Implications for future research and policy development are discussed.