HBTBD: A Heterogeneous Bitcoin Transaction Behavior Dataset for Anti-Money Laundering
In this paper, we predict money laundering in Bitcoin transactions by leveraging a deep learning framework and incorporating more characteristics of Bitcoin transactions. We produced a dataset containing 46,045 Bitcoin transaction entities and 319,311 Bitcoin wallet addresses associated with them. W...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-07-01
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| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/13/15/8766 |
| _version_ | 1827731447380705280 |
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| author | Jialin Song Yijun Gu |
| author_facet | Jialin Song Yijun Gu |
| author_sort | Jialin Song |
| collection | DOAJ |
| description | In this paper, we predict money laundering in Bitcoin transactions by leveraging a deep learning framework and incorporating more characteristics of Bitcoin transactions. We produced a dataset containing 46,045 Bitcoin transaction entities and 319,311 Bitcoin wallet addresses associated with them. We aggregated this information to form a heterogeneous graph dataset and propose three metapath representations around transaction entities, which enrich the characteristics of Bitcoin transactions. Then, we designed a metapath encoder and integrated it into a heterogeneous graph node embedding method. The experimental results indicate that our proposed framework significantly improves the accuracy of illicit Bitcoin transaction recognition compared with traditional methods. Therefore, our proposed framework is more conducive in detecting money laundering activities in Bitcoin transactions. |
| first_indexed | 2024-03-11T00:31:25Z |
| format | Article |
| id | doaj.art-7b2f5abc50384f29a8492ae0533e6e7c |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-11T00:31:25Z |
| publishDate | 2023-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-7b2f5abc50384f29a8492ae0533e6e7c2023-11-18T22:37:14ZengMDPI AGApplied Sciences2076-34172023-07-011315876610.3390/app13158766HBTBD: A Heterogeneous Bitcoin Transaction Behavior Dataset for Anti-Money LaunderingJialin Song0Yijun Gu1School of Information Network Security, People’s Public Security University of China, Beijing 100032, ChinaSchool of Information Network Security, People’s Public Security University of China, Beijing 100032, ChinaIn this paper, we predict money laundering in Bitcoin transactions by leveraging a deep learning framework and incorporating more characteristics of Bitcoin transactions. We produced a dataset containing 46,045 Bitcoin transaction entities and 319,311 Bitcoin wallet addresses associated with them. We aggregated this information to form a heterogeneous graph dataset and propose three metapath representations around transaction entities, which enrich the characteristics of Bitcoin transactions. Then, we designed a metapath encoder and integrated it into a heterogeneous graph node embedding method. The experimental results indicate that our proposed framework significantly improves the accuracy of illicit Bitcoin transaction recognition compared with traditional methods. Therefore, our proposed framework is more conducive in detecting money laundering activities in Bitcoin transactions.https://www.mdpi.com/2076-3417/13/15/8766graph embeddingBitcoin anti-money launderingmachine learningheterogeneous graph neural networksmetapath encoder |
| spellingShingle | Jialin Song Yijun Gu HBTBD: A Heterogeneous Bitcoin Transaction Behavior Dataset for Anti-Money Laundering Applied Sciences graph embedding Bitcoin anti-money laundering machine learning heterogeneous graph neural networks metapath encoder |
| title | HBTBD: A Heterogeneous Bitcoin Transaction Behavior Dataset for Anti-Money Laundering |
| title_full | HBTBD: A Heterogeneous Bitcoin Transaction Behavior Dataset for Anti-Money Laundering |
| title_fullStr | HBTBD: A Heterogeneous Bitcoin Transaction Behavior Dataset for Anti-Money Laundering |
| title_full_unstemmed | HBTBD: A Heterogeneous Bitcoin Transaction Behavior Dataset for Anti-Money Laundering |
| title_short | HBTBD: A Heterogeneous Bitcoin Transaction Behavior Dataset for Anti-Money Laundering |
| title_sort | hbtbd a heterogeneous bitcoin transaction behavior dataset for anti money laundering |
| topic | graph embedding Bitcoin anti-money laundering machine learning heterogeneous graph neural networks metapath encoder |
| url | https://www.mdpi.com/2076-3417/13/15/8766 |
| work_keys_str_mv | AT jialinsong hbtbdaheterogeneousbitcointransactionbehaviordatasetforantimoneylaundering AT yijungu hbtbdaheterogeneousbitcointransactionbehaviordatasetforantimoneylaundering |