BACH: A Tool for Analyzing Blockchain Transactions Using Address Clustering Heuristics
Cryptocurrencies have now become an emerging blockchain-based payment technology; among them, bitcoin is the best known and most widely used. Users on these networks are pseudo-anonymous, meaning that while all transactions from an address are transparent and searchable by anyone, the users’ true id...
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MDPI AG
2024-09-01
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| Online Access: | https://www.mdpi.com/2078-2489/15/10/589 |
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| author | Michele Caringella Francesco Violante Francesco De Lucci Stefano Galantucci Matteo Costantini |
| author_facet | Michele Caringella Francesco Violante Francesco De Lucci Stefano Galantucci Matteo Costantini |
| author_sort | Michele Caringella |
| collection | DOAJ |
| description | Cryptocurrencies have now become an emerging blockchain-based payment technology; among them, bitcoin is the best known and most widely used. Users on these networks are pseudo-anonymous, meaning that while all transactions from an address are transparent and searchable by anyone, the users’ true identities are not directly revealed; to preserve their privacy, users often use many different addresses. In recent years, some studies have been conducted regarding analyzing clusters of bitcoin addresses that, according to certain heuristics, belong to the same entity. This capability provides law enforcement with valuable information for investigating illegal activities involving cryptocurrencies. Clustering methods that rely on a single heuristic often fail to accurately and comprehensively cluster multiple addresses. This paper proposes <i>Bitcoin Address Clustering based on multiple Heuristics</i> (BACH): a tool that uses three different clustering heuristics to identify clusters of bitcoin addresses, which are displayed through a three-dimensional graph. The results lead to several analyses, including a comparative evaluation of WalletExplorer, which is a similar address clustering tool. BACH introduces the innovative feature of visualizing the internal structure of clusters in a graphical format. The study also shows how the combined use of different heuristics provides better results and more complete clusters than those obtained from their individual use. |
| format | Article |
| id | doaj-art-7cc1d8237b884610a64b7103fc52f2a6 |
| institution | OA Journals |
| issn | 2078-2489 |
| language | English |
| publishDate | 2024-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Information |
| spelling | doaj-art-7cc1d8237b884610a64b7103fc52f2a62025-08-20T02:11:04ZengMDPI AGInformation2078-24892024-09-01151058910.3390/info15100589BACH: A Tool for Analyzing Blockchain Transactions Using Address Clustering HeuristicsMichele Caringella0Francesco Violante1Francesco De Lucci2Stefano Galantucci3Matteo Costantini4Italpaghe S.r.l., Viale Paolo Borsellino e Giovanni Falcone, 17, 70125 Bari, ItalyItalpaghe S.r.l., Viale Paolo Borsellino e Giovanni Falcone, 17, 70125 Bari, ItalyItalpaghe S.r.l., Viale Paolo Borsellino e Giovanni Falcone, 17, 70125 Bari, ItalyDepartment of Computer Science, University of Bari Aldo Moro, 70125 Bari, ItalyDepartment of Computer Science, University of Bari Aldo Moro, 70125 Bari, ItalyCryptocurrencies have now become an emerging blockchain-based payment technology; among them, bitcoin is the best known and most widely used. Users on these networks are pseudo-anonymous, meaning that while all transactions from an address are transparent and searchable by anyone, the users’ true identities are not directly revealed; to preserve their privacy, users often use many different addresses. In recent years, some studies have been conducted regarding analyzing clusters of bitcoin addresses that, according to certain heuristics, belong to the same entity. This capability provides law enforcement with valuable information for investigating illegal activities involving cryptocurrencies. Clustering methods that rely on a single heuristic often fail to accurately and comprehensively cluster multiple addresses. This paper proposes <i>Bitcoin Address Clustering based on multiple Heuristics</i> (BACH): a tool that uses three different clustering heuristics to identify clusters of bitcoin addresses, which are displayed through a three-dimensional graph. The results lead to several analyses, including a comparative evaluation of WalletExplorer, which is a similar address clustering tool. BACH introduces the innovative feature of visualizing the internal structure of clusters in a graphical format. The study also shows how the combined use of different heuristics provides better results and more complete clusters than those obtained from their individual use.https://www.mdpi.com/2078-2489/15/10/589bitcoinaddress clusteringblockchainanonymityheuristics |
| spellingShingle | Michele Caringella Francesco Violante Francesco De Lucci Stefano Galantucci Matteo Costantini BACH: A Tool for Analyzing Blockchain Transactions Using Address Clustering Heuristics Information bitcoin address clustering blockchain anonymity heuristics |
| title | BACH: A Tool for Analyzing Blockchain Transactions Using Address Clustering Heuristics |
| title_full | BACH: A Tool for Analyzing Blockchain Transactions Using Address Clustering Heuristics |
| title_fullStr | BACH: A Tool for Analyzing Blockchain Transactions Using Address Clustering Heuristics |
| title_full_unstemmed | BACH: A Tool for Analyzing Blockchain Transactions Using Address Clustering Heuristics |
| title_short | BACH: A Tool for Analyzing Blockchain Transactions Using Address Clustering Heuristics |
| title_sort | bach a tool for analyzing blockchain transactions using address clustering heuristics |
| topic | bitcoin address clustering blockchain anonymity heuristics |
| url | https://www.mdpi.com/2078-2489/15/10/589 |
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