From Ledger to P2P Network: De-anonymization on Bitcoin Using Cross-Layer Analysis

Che Zheng, Meng Shen, Junxian Duan, Liehuang Zhu

Abstract: Cryptocurrency has the characteristics of decentralization and anonymization, which have emerged and attracted widespread attention from various parties. However, cryptocurrency anonymization breeds illegal activities such as money laundering, gambling, and phishing. Thus, it is essential to deanonymity on Cryptocurrency transactions. This paper proposes a cross-layer analysis method for Bitcoin transactions deanonymization. Through acquiring large-scale original transaction information and combining the characteristics of the network layer and the transaction layer, we propose a propagation pattern extraction model and associated address clustering model. We achieve the matching of the suspected transaction with the originator’s IP address for high precision and low overhead. Through experimental analysis in a real Bitcoin system, the cross-layer method can effectively match the original transaction with the target node, which reaches an accuracy of 81.3% and is 30% higher than the state-of-the-art method. By controlling several factors, such as different times and nodes, the characteristics of the extracted transaction propagation pattern can be proved reasonable and reliable. The practicality and effectiveness of the cross-layer analysis are higher than that of a single-level scheme.