Characterizing Entities in the Bitcoin Blockchain

TL;DR

This paper investigates how transaction patterns in the Bitcoin blockchain can reveal information about entities, demonstrating that even limited data mining can effectively characterize user identities and behaviors.

Contribution

The study introduces new features based on transaction neighborhood patterns and evaluates their effectiveness in entity characterization on the Bitcoin blockchain.

Findings

Transaction neighborhood features can leak entity information.

Even weak attackers can successfully characterize entities.

New features improve understanding of privacy risks in Bitcoin.

Abstract

Bitcoin has created a new exchange paradigm within which financial transactions can be trusted without an intermediary. This premise of a free decentralized transactional network however requires, in its current implementation, unrestricted access to the ledger for peer-based transaction verification. A number of studies have shown that, in this pseudonymous context, identities can be leaked based on transaction features or off-network information. In this work, we analyze the information revealed by the pattern of transactions in the neighborhood of a given entity transaction. By definition, these features which pertain to an extended network are not directly controllable by the entity, but might enable leakage of information about transacting entities. We define a number of new features relevant to entity characterization on the Bitcoin Blockchain and study their efficacy in practice. We show that even a weak attacker with shallow data mining knowledge is able to leverage these features to characterize the entity properties.