Bitcoin allows users to benefit from pseudonymity, by generating an
arbitrary number of aliases (or addresses) to move funds. However, the
complete history of all transactions ever performed in the network is public.
In this thesis we present a modular framework, BitIodine, which parses
the blockchain, clusters addresses that are likely to belong to a same
user or group of users, classifies such users and labels them, and
visualizes complex information extracted from the network.
We tested BitIodine on several real-world use cases, finding early links
between the founder of the Silk Road and cold wallets exceeding 111,114 BTC.
In another example, we investigated the CryptoLocker ransomware,
accurately quantifying the number of ransoms paid and extracting information
about the victims.