An Analysis of Anonymity in Bitcoin Using P2P Network Traffic

Over the last 4 years, Bitcoin, a decentralized P2P crypto-currency, has gained widespread attention. The ability to create pseudo-anonymous financial transactions using bitcoins has made the currency attractive to users who value their privacy. Although previous work has analyzed the degree of anonymity Bitcoin offers using clustering and flow analysis, none have demonstrated the ability to map Bitcoin addresses directly to IP data. We propose a novel approach to creating and evaluating such mappings solely using real-time transaction traffic collected over 5 months. We developed heuristics for identifying ownership relationships between Bitcoin addresses and IP addresses. We discuss the circumstances under which these relationships become apparent and demonstrate how nearly 1,000 Bitcoin addresses can be mapped to their likely owner IPs by leveraging anomalous relaying behavior.