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Pattern Analysis of Money Flow in the Bitcoin Blockchain

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  • Natkamon Tovanich

    (CREST - Centre de Recherche en Économie et Statistique - ENSAI - Ecole Nationale de la Statistique et de l'Analyse de l'Information [Bruz] - X - École polytechnique - ENSAE Paris - École Nationale de la Statistique et de l'Administration Économique - CNRS - Centre National de la Recherche Scientifique, X - École polytechnique)

  • Rémy Cazabet

    (DM2L - Data Mining and Machine Learning - LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information - UL2 - Université Lumière - Lyon 2 - ECL - École Centrale de Lyon - Université de Lyon - UCBL - Université Claude Bernard Lyon 1 - Université de Lyon - INSA Lyon - Institut National des Sciences Appliquées de Lyon - Université de Lyon - INSA - Institut National des Sciences Appliquées - CNRS - Centre National de la Recherche Scientifique, LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information - UL2 - Université Lumière - Lyon 2 - ECL - École Centrale de Lyon - Université de Lyon - UCBL - Université Claude Bernard Lyon 1 - Université de Lyon - INSA Lyon - Institut National des Sciences Appliquées de Lyon - Université de Lyon - INSA - Institut National des Sciences Appliquées - CNRS - Centre National de la Recherche Scientifique, UCBL - Université Claude Bernard Lyon 1 - Université de Lyon, IXXI - Institut Rhône-Alpin des systèmes complexes - ENS de Lyon - École normale supérieure de Lyon - UL2 - Université Lumière - Lyon 2 - UJML - Université Jean Moulin - Lyon 3 - Université de Lyon - UCBL - Université Claude Bernard Lyon 1 - Université de Lyon - INSA Lyon - Institut National des Sciences Appliquées de Lyon - Université de Lyon - INSA - Institut National des Sciences Appliquées - Inria - Institut National de Recherche en Informatique et en Automatique - CNRS - Centre National de la Recherche Scientifique - UGA - Université Grenoble Alpes)

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.

Suggested Citation

  • Natkamon Tovanich & Rémy Cazabet, 2022. "Pattern Analysis of Money Flow in the Bitcoin Blockchain," Post-Print hal-03896866, HAL.
    • Handle: RePEc:hal:journl:hal-03896866
    DOI: 10.1007/978-3-031-21127-0_36
    Note: View the original document on HAL open archive server: https://hal.science/hal-03896866
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    References listed on IDEAS

    as
    1. Natkamon Tovanich & Nicolas Soulié & Nicolas Heulot & Petra Isenberg, 2022. "The evolution of mining pools and miners’ behaviors in the Bitcoin blockchain," Post-Print hal-03610424, HAL.
    2. Matthias Lischke & Benjamin Fabian, 2016. "Analyzing the Bitcoin Network: The First Four Years," Future Internet, MDPI, vol. 8(1), pages 1-40, March.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Bitcoin; Money flow; Taint analysis; Graph embeddings;
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