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Social Network Analysis and Mining
Published in:

01-12-2020 | Original Article

An ego network analysis of sextortionists

Authors: Frédérique Oggier, Anwitaman Datta, Silivanxay Phetsouvanh

Published in: Social Network Analysis and Mining | Issue 1/2020

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Abstract

We consider a particular instance of user interactions in the Bitcoin network, that of interactions among wallet addresses belonging to scammers. Aggregation of multiple inputs and change addresses are common heuristics used to establish relationships among addresses and analyze transaction amounts in the Bitcoin network. We propose a flow centric approach that complements such heuristics, by studying the branching, merger and propagation of Bitcoin flows. We study a recent sextortion campaign by exploring the ego network of known offending wallet addresses. We compare and combine different existing and new heuristics, which allows us to identify (1) Bitcoin addresses of interest (including possible recurrent go-to addresses for the scammers) and (2) relevant Bitcoin flows, from scam Bitcoin addresses to a Binance exchange and to other other scam addresses, that suggest connections among prima facie disparate waves of similar scams.
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Appendix
Available only for authorised users
Footnotes
1
The curated ego network dataset used in this paper can be found at Oggier et al. (2019).
 
2
Our tool uses the Python library Beautifulsoup4.
 
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Metadata
Title
An ego network analysis of sextortionists
Authors
Frédérique Oggier
Anwitaman Datta
Silivanxay Phetsouvanh
Publication date
01-12-2020
Publisher
Springer Vienna
Published in
Social Network Analysis and Mining / Issue 1/2020
Print ISSN: 1869-5450
Electronic ISSN: 1869-5469
DOI
https://doi.org/10.1007/s13278-020-00650-x

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