EGRET : extortion graph exploration techniques in the Bitcoin network

• Main Authors: Phetsouvanh, Silivanxay, Oggier, Frédérique, Datta, Anwitaman
• 其他作者: School of Computer Science and Engineering
• 格式: Conference or Workshop Item
• 語言: English
• 出版: 2019
• 主題: Bitcoin Forensics; Graph Analysis; DRNTU::Engineering::Computer science and engineering
• 在線閱讀: https://hdl.handle.net/10356/88894; http://hdl.handle.net/10220/49145; https://doi.org/10.21979/N9/FHBR2E
• 機構: Nanyang Technological University

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.