EGRET : extortion graph exploration techniques in the Bitcoin network
The Bitcoin network is a complex network that records anonymous financial transactions while encapsulating the relationships among its pseudonymous users. This paper proposes graph mining techniques to explore the relationships among wallet addresses (pseudonyms for Bitcoin users) suspected to be in...
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| Format: | Conference Paper |
| Language: | English |
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2019
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| Online Access: | https://hdl.handle.net/10356/88894 http://hdl.handle.net/10220/49145 |
| _version_ | 1826122088342093824 |
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| author | Phetsouvanh, Silivanxay Oggier, Frédérique Datta, Anwitaman |
| author2 | School of Computer Science and Engineering |
| author_facet | School of Computer Science and Engineering Phetsouvanh, Silivanxay Oggier, Frédérique Datta, Anwitaman |
| author_sort | Phetsouvanh, Silivanxay |
| collection | NTU |
| description | The Bitcoin network is a complex network that records anonymous financial transactions while encapsulating the relationships among its pseudonymous users. This paper proposes graph mining techniques to explore the relationships among wallet addresses (pseudonyms for Bitcoin users) suspected to be involved in a given extortion racket, exploiting the anonymity of the Bitcoin network to collect and launder money. Starting around Bitcoin addresses of potential interest, neighborhood subgraphs are analyzed in terms of path length and confluence to detect suspicious Bitcoin flow and other wallet addresses controlled by the suspected perpetrators. We show with a dataset of the Ashley Madison blackmail campaign from August 2015 how the mechanisms can be used both to estimate the amount of money that was extorted by the suspected perpetrators under the specific blackmail campaign, and also estimate the amount of money handled by them during the same period of time. |
| first_indexed | 2024-10-01T05:42:47Z |
| format | Conference Paper |
| id | ntu-10356/88894 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T05:42:47Z |
| publishDate | 2019 |
| record_format | dspace |
| spelling | ntu-10356/888942023-02-28T19:17:38Z EGRET : extortion graph exploration techniques in the Bitcoin network Phetsouvanh, Silivanxay Oggier, Frédérique Datta, Anwitaman School of Computer Science and Engineering School of Physical and Mathematical Sciences Proceedings of 2018 IEEE International Conference on Data Mining Workshops (ICDMW) Bitcoin Forensics Graph Analysis DRNTU::Engineering::Computer science and engineering The Bitcoin network is a complex network that records anonymous financial transactions while encapsulating the relationships among its pseudonymous users. This paper proposes graph mining techniques to explore the relationships among wallet addresses (pseudonyms for Bitcoin users) suspected to be involved in a given extortion racket, exploiting the anonymity of the Bitcoin network to collect and launder money. Starting around Bitcoin addresses of potential interest, neighborhood subgraphs are analyzed in terms of path length and confluence to detect suspicious Bitcoin flow and other wallet addresses controlled by the suspected perpetrators. We show with a dataset of the Ashley Madison blackmail campaign from August 2015 how the mechanisms can be used both to estimate the amount of money that was extorted by the suspected perpetrators under the specific blackmail campaign, and also estimate the amount of money handled by them during the same period of time. Accepted version 2019-07-05T02:40:45Z 2019-12-06T17:13:14Z 2019-07-05T02:40:45Z 2019-12-06T17:13:14Z 2018-11-01 2018 Conference Paper Phetsouvanh, S., Oggier, F., & Datta, A. (2018). EGRET : extortion graph exploration techniques in the Bitcoin network. Proceedings of 2018 IEEE International Conference on Data Mining Workshops (ICDMW). doi:10.1109/ICDMW.2018.00043 https://hdl.handle.net/10356/88894 http://hdl.handle.net/10220/49145 10.1109/ICDMW.2018.00043 208885 en https://doi.org/10.21979/N9/FHBR2E © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: https://doi.org/10.1109/ICDMW.2018.00043 8 p. application/pdf |
| spellingShingle | Bitcoin Forensics Graph Analysis DRNTU::Engineering::Computer science and engineering Phetsouvanh, Silivanxay Oggier, Frédérique Datta, Anwitaman EGRET : extortion graph exploration techniques in the Bitcoin network |
| title | EGRET : extortion graph exploration techniques in the Bitcoin network |
| title_full | EGRET : extortion graph exploration techniques in the Bitcoin network |
| title_fullStr | EGRET : extortion graph exploration techniques in the Bitcoin network |
| title_full_unstemmed | EGRET : extortion graph exploration techniques in the Bitcoin network |
| title_short | EGRET : extortion graph exploration techniques in the Bitcoin network |
| title_sort | egret extortion graph exploration techniques in the bitcoin network |
| topic | Bitcoin Forensics Graph Analysis DRNTU::Engineering::Computer science and engineering |
| url | https://hdl.handle.net/10356/88894 http://hdl.handle.net/10220/49145 |
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