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The Complex Community Structure of the Bitcoin Address Correspondence Network


Fischer, Jan Alexander; Palechor, Andres; Dell’Aglio, Daniele; Bernstein, Abraham; Tessone, Claudio J (2021). The Complex Community Structure of the Bitcoin Address Correspondence Network. Frontiers in Physics, 9:681798.

Abstract

Bitcoin is built on a blockchain, an immutable decentralized ledger that allows entities (users) to exchange Bitcoins in a pseudonymous manner. Bitcoins are associated with alpha-numeric addresses and are transferred via transactions. Each transaction is composed of a set of input addresses (associated with unspent outputs received from previous transactions) and a set of output addresses (to which Bitcoins are transferred). Despite Bitcoin was designed with anonymity in mind, different heuristic approaches exist to detect which addresses in a specific transaction belong to the same entity. By applying these heuristics, we build an Address Correspondence Network: in this representation, addresses are nodes are connected with edges if at least one heuristic detects them as belonging to the same entity. In this paper, we analyze for the first time the Address Correspondence Network and show it is characterized by a complex topology, signaled by a broad, skewed degree distribution and a power-law component size distribution. Using a large-scale dataset of addresses for which the controlling entities are known, we show that a combination of external data coupled with standard community detection algorithms can reliably identify entities. The complex nature of the Address Correspondence Network reveals that usage patterns of individual entities create statistical regularities; and that these regularities can be leveraged to more accurately identify entities and gain a deeper understanding of the Bitcoin economy as a whole.

Abstract

Bitcoin is built on a blockchain, an immutable decentralized ledger that allows entities (users) to exchange Bitcoins in a pseudonymous manner. Bitcoins are associated with alpha-numeric addresses and are transferred via transactions. Each transaction is composed of a set of input addresses (associated with unspent outputs received from previous transactions) and a set of output addresses (to which Bitcoins are transferred). Despite Bitcoin was designed with anonymity in mind, different heuristic approaches exist to detect which addresses in a specific transaction belong to the same entity. By applying these heuristics, we build an Address Correspondence Network: in this representation, addresses are nodes are connected with edges if at least one heuristic detects them as belonging to the same entity. In this paper, we analyze for the first time the Address Correspondence Network and show it is characterized by a complex topology, signaled by a broad, skewed degree distribution and a power-law component size distribution. Using a large-scale dataset of addresses for which the controlling entities are known, we show that a combination of external data coupled with standard community detection algorithms can reliably identify entities. The complex nature of the Address Correspondence Network reveals that usage patterns of individual entities create statistical regularities; and that these regularities can be leveraged to more accurately identify entities and gain a deeper understanding of the Bitcoin economy as a whole.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Informatics
Dewey Decimal Classification:000 Computer science, knowledge & systems
Scopus Subject Areas:Life Sciences > Biophysics
Physical Sciences > Materials Science (miscellaneous)
Physical Sciences > Mathematical Physics
Physical Sciences > General Physics and Astronomy
Physical Sciences > Physical and Theoretical Chemistry
Uncontrolled Keywords:Physical and Theoretical Chemistry, General Physics and Astronomy, Mathematical Physics, Materials Science (miscellaneous), Biophysics
Language:English
Date:30 June 2021
Deposited On:03 Sep 2021 11:20
Last Modified:04 Sep 2021 20:00
Publisher:Frontiers Research Foundation
ISSN:2296-424X
OA Status:Gold
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.3389/fphy.2021.681798
Project Information:
  • : FunderSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
  • : Grant ID
  • : Project Title
  • : FunderUniversität Zürich
  • : Grant ID
  • : Project Title

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