Please use this identifier to cite or link to this item:
|Title:||EGRET : extortion graph exploration techniques in the Bitcoin network||Authors:||Phetsouvanh, Silivanxay
DRNTU::Engineering::Computer science and engineering
|Issue Date:||2018||Source:||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||Abstract:||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.||URI:||https://hdl.handle.net/10356/88894
|DOI:||https://dx.doi.org/10.1109/ICDMW.2018.00043||Rights:||© 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||metadata.item.grantfulltext:||open||metadata.item.fulltext:||With Fulltext|
|Appears in Collections:||SCSE Conference Papers|
SPMS Conference Papers
Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.