Pattern Analysis of Money Flows in the Bitcoin Blockchain

Abstract

Bitcoin is the first and highest valued cryptocurrency that stores transactions in a publicly distributed ledger called the blockchain. Understanding the activity and behavior of Bitcoin actors is a crucial research topic as they are pseudonymous in the transaction network. In this article, we propose a method based on taint analysis to extract taint flows-dynamic networks representing the sequence of Bitcoins transferred from an initial source to other actors until dissolution. Then, we apply graph embedding methods to characterize taint flows. We evaluate our embedding method with taint flows from top mining pools and show that it can classify mining pools with high accuracy. We also found that taint flows from the same period show high similarity. Our work proves that tracing the money flows can be a promising approach to classifying source actors and characterizing different money flow patterns.

The nilcatenation problem and its application for detecting money laundering activities in cryptocurrency networks

“…Other applications of Bitcoin blockchain analysis include understanding the behavior of Bitcoin actors and detecting mining pools (Tovanich and Cazabet, 2023) and the identification of core nodes associated with ransomware attacks (Turner et al., 2021).…”