  Cryptocurrencies gained lots of attention mainly because of the anonymous way
of online payment, which they suggested. Meanwhile, Bitcoin and other major
cryptocurrencies have experienced severe deanonymization attacks. To address
these attacks, Bitcoin contributors introduced services called mixers or
tumblers. Mixing or laundry services aim to return anonymity back to the
network. In this research, we tackle the problem of losing the footprint of
money in Bitcoin and other cryptocurrencies networks caused by the usage of
mixing services. We devise methods to track transactions and addresses of these
services and the addresses of dirty and cleaned money. Because of the lack of
labeled data, we had to transact with these services and prepare labeled data.
Using this data, we found reliable patterns and developed an integrated
algorithm to detect mixing transactions, mixing addresses, sender addresses,
and receiver addresses in the Bitcoin network.
