Please use this identifier to cite or link to this item:
https://hdl.handle.net/10356/88895
Title: | BiVA : Bitcoin network visualization & analysis | Authors: | Oggier, Frédérique Phetsouvanh, Silivanxay Datta, Anwitaman |
Keywords: | Bitcoin Forensics Graph Analysis DRNTU::Engineering::Computer science and engineering |
Issue Date: | 2018 | Source: | Oggier, F., Phetsouvanh, S., & Datta, A. (2018). BiVA : Bitcoin network visualization & analysis. Proceedings of 2018 IEEE International Conference on Data Mining Workshops (ICDMW). doi:10.1109/ICDMW.2018.00210 | Conference: | Proceedings of 2018 IEEE International Conference on Data Mining Workshops (ICDMW) | Abstract: | We showcase a graph mining tool, BiVA, for visualization and analysis of the Bitcoin network. It enables data exploration, visualization of subgraphs around nodes of interest, and integrates both standard and new algorithms, including a general algorithm for flow based clustering for directed graphs, and other Bitcoin network specific wallet address aggregation mechanisms. The BiVA user interface makes it easy to get started with a basic visualization that gives insights into nodes of interests, and the tool is modular, allowing easy integration of new algorithms. Its functionalities are demonstrated with a case study of extortion of Ashley Madison data breach victims. | URI: | https://hdl.handle.net/10356/88895 http://hdl.handle.net/10220/48917 |
DOI: | 10.1109/ICDMW.2018.00210 | DOI (Related Dataset): | https://doi.org/10.21979/N9/FHBR2E | Schools: | School of Computer Science and Engineering School of Physical and Mathematical Sciences |
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.2018.00210 | Fulltext Permission: | open | Fulltext Availability: | With Fulltext |
Appears in Collections: | SCSE Conference Papers SPMS Conference Papers |
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Cameraready-BiVA.pdf | 1.54 MB | Adobe PDF | View/Open |
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