Multi-input address incremental clustering for the Bitcoin blockchain based on Petri net model analysis
Bitcoin is a cryptocurrency based on blockchain. All historical Bitcoin transactions are stored in the Bitcoin blockchain, but Bitcoin owners are generally unknown. This is the reason for Bitcoin's pseudo-anonymity, therefore it is often used for illegal transactions. Bitcoin addresses are rela...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
KeAi Communications Co., Ltd.
2022-10-01
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| Series: | Digital Communications and Networks |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S235286482200178X |
| _version_ | 1811225510264438784 |
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| author | Fangchi Qin Yan Wu Fang Tao Lu Liu Leilei Shi Anthony J. Miller |
| author_facet | Fangchi Qin Yan Wu Fang Tao Lu Liu Leilei Shi Anthony J. Miller |
| author_sort | Fangchi Qin |
| collection | DOAJ |
| description | Bitcoin is a cryptocurrency based on blockchain. All historical Bitcoin transactions are stored in the Bitcoin blockchain, but Bitcoin owners are generally unknown. This is the reason for Bitcoin's pseudo-anonymity, therefore it is often used for illegal transactions. Bitcoin addresses are related to Bitcoin users' identities. Some Bitcoin addresses have the potential to be analyzed due to the behavior patterns of Bitcoin transactions. However, existing Bitcoin analysis methods do not consider the fusion of new blocks' data, resulting in low efficiency of Bitcoin address analysis. In order to address this problem, this paper proposes an incremental Bitcoin address cluster method to avoid re-clustering when new block data is added. Besides, a heuristic Bitcoin address clustering algorithm is developed to improve clustering accuracy for the Bitcoin Blockchain. Experimental results show that the proposed method increases Bitcoin address cluster efficiency and accuracy. |
| first_indexed | 2024-04-12T09:07:21Z |
| format | Article |
| id | doaj.art-92c27740b917407f99ab81aa5b6edd63 |
| institution | Directory Open Access Journal |
| issn | 2352-8648 |
| language | English |
| last_indexed | 2024-04-12T09:07:21Z |
| publishDate | 2022-10-01 |
| publisher | KeAi Communications Co., Ltd. |
| record_format | Article |
| series | Digital Communications and Networks |
| spelling | doaj.art-92c27740b917407f99ab81aa5b6edd632022-12-22T03:39:03ZengKeAi Communications Co., Ltd.Digital Communications and Networks2352-86482022-10-0185680686Multi-input address incremental clustering for the Bitcoin blockchain based on Petri net model analysisFangchi Qin0Yan Wu1Fang Tao2Lu Liu3Leilei Shi4Anthony J. Miller5Jiangsu Key Laboratory of Security Technology for Industrial Cyberspace, School of Computer Science and Telecommunication Engineering, Jiangsu University, ChinaJiangsu Key Laboratory of Security Technology for Industrial Cyberspace, School of Computer Science and Telecommunication Engineering, Jiangsu University, China; Corresponding author.Birmingham Business School, University of Birmingham, UKSchool of Informatics, University of Leicester, UK; Corresponding author.Jiangsu Key Laboratory of Security Technology for Industrial Cyberspace, School of Computer Science and Telecommunication Engineering, Jiangsu University, ChinaSchool of Informatics, University of Leicester, UKBitcoin is a cryptocurrency based on blockchain. All historical Bitcoin transactions are stored in the Bitcoin blockchain, but Bitcoin owners are generally unknown. This is the reason for Bitcoin's pseudo-anonymity, therefore it is often used for illegal transactions. Bitcoin addresses are related to Bitcoin users' identities. Some Bitcoin addresses have the potential to be analyzed due to the behavior patterns of Bitcoin transactions. However, existing Bitcoin analysis methods do not consider the fusion of new blocks' data, resulting in low efficiency of Bitcoin address analysis. In order to address this problem, this paper proposes an incremental Bitcoin address cluster method to avoid re-clustering when new block data is added. Besides, a heuristic Bitcoin address clustering algorithm is developed to improve clustering accuracy for the Bitcoin Blockchain. Experimental results show that the proposed method increases Bitcoin address cluster efficiency and accuracy.http://www.sciencedirect.com/science/article/pii/S235286482200178XBitcoinBlockchainPetri netIncremental clustering |
| spellingShingle | Fangchi Qin Yan Wu Fang Tao Lu Liu Leilei Shi Anthony J. Miller Multi-input address incremental clustering for the Bitcoin blockchain based on Petri net model analysis Digital Communications and Networks Bitcoin Blockchain Petri net Incremental clustering |
| title | Multi-input address incremental clustering for the Bitcoin blockchain based on Petri net model analysis |
| title_full | Multi-input address incremental clustering for the Bitcoin blockchain based on Petri net model analysis |
| title_fullStr | Multi-input address incremental clustering for the Bitcoin blockchain based on Petri net model analysis |
| title_full_unstemmed | Multi-input address incremental clustering for the Bitcoin blockchain based on Petri net model analysis |
| title_short | Multi-input address incremental clustering for the Bitcoin blockchain based on Petri net model analysis |
| title_sort | multi input address incremental clustering for the bitcoin blockchain based on petri net model analysis |
| topic | Bitcoin Blockchain Petri net Incremental clustering |
| url | http://www.sciencedirect.com/science/article/pii/S235286482200178X |
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