De anonymization of Bitcoin addresses based on concept lattice

Abstract

This study aims to explore a method for the de-anonymization of Bitcoin addresses based on Formal Concept Analysis (FCA).Although Bitcoin, as a decentralized cryptocurrency, offers user privacy protection, its anonymity has also been exploited by criminals, leading to an increase in illegal activities such as money laundering and terrorist financing.To address this challenge, we propose a novel deanonymization framework that constructs a formal context using Bitcoin transaction data and generates the corresponding concept lattice.By extracting the attribute weight vectors for each category, our model can effectively classify Bitcoin addresses, thereby identifying potential high-risk addresses.