An Analysis of Anonymity in the Bitcoin System

TL;DR

This paper examines the complex issue of user anonymity in Bitcoin by analyzing the topological structure of networks derived from transaction history and exploring implications for de-anonymization and privacy.

Contribution

It introduces a topological analysis of Bitcoin transaction networks and demonstrates how combining network structures with external data can de-anonymize users.

Findings

Bitcoin networks have non-trivial topological structures

External information can be combined with network analysis for de-anonymization

The approach can identify users involved in specific transactions like thefts

Abstract

Anonymity in Bitcoin, a peer-to-peer electronic currency system, is a complicated issue. Within the system, users are identified by public-keys only. An attacker wishing to de-anonymize its users will attempt to construct the one-to-many mapping between users and public-keys and associate information external to the system with the users. Bitcoin tries to prevent this attack by storing the mapping of a user to his or her public-keys on that user's node only and by allowing each user to generate as many public-keys as required. In this chapter we consider the topological structure of two networks derived from Bitcoin's public transaction history. We show that the two networks have a non-trivial topological structure, provide complementary views of the Bitcoin system and have implications for anonymity. We combine these structures with external information and techniques such as context discovery and flow analysis to investigate an alleged theft of Bitcoins, which, at the time of the theft, had a market value of approximately half a million U.S. dollars.