Detecting Anomalous Cryptocurrency Transactions: an AML/CFT Application of Machine Learning-based Forensics. (arXiv:2206.04803v1 [cs.CR])

The rise of blockchain and distributed ledger technologies (DLTs) in the
financial sector has generated a socio-economic shift that triggered legal
concerns and regulatory initiatives. While the anonymity of DLTs may safeguard
the right to privacy, data protection and other civil liberties, lack of
identification hinders accountability, investigation and enforcement. The
resulting challenges extend to the rules to combat money laundering and the
financing of terrorism and proliferation (AML/CFT). As law enforcement agencies
and analytics companies have begun to successfully …

aml application cryptocurrency forensics machine machine learning