How to Not Get Caught When You Launder Money on Blockchain?
This addresses the challenge of preventing e-crime for blockchain users and regulators, but it is incremental as it critiques current methods without presenting a new solution.
The paper tackles the problem of money laundering detection on blockchains by arguing that certain strategies can make it virtually undetectable with existing AI tools, highlighting the need for novel analytic methods in AI to combat e-crime effectively.
The number of blockchain users has tremendously grown in recent years. As an unintended consequence, e-crime transactions on blockchains has been on the rise. Consequently, public blockchains have become a hotbed of research for developing AI tools to detect and trace users and transactions that are related to e-crime. We argue that following a few select strategies can make money laundering on blockchain virtually undetectable with most of the existing tools and algorithms. As a result, the effective combating of e-crime activities involving cryptocurrencies requires the development of novel analytic methodology in AI.