  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.
