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Social Network Analysis and Mining
Erschienen in: Social Network Analysis and Mining 1/2020

01.12.2020 | Original Article

An ego network analysis of sextortionists

Erschienen in: Social Network Analysis and Mining | Ausgabe 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.
Vorheriger Artikel A comparative analysis of similarity measures akin to the Jaccard index in collaborative recommendations: empirical and theoretical perspective
Nächster Artikel Neutrality may matter: sentiment analysis in reviews of Airbnb, Booking, and Couchsurfing in Brazil and USA

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Fußnoten
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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Metadaten
Titel
An ego network analysis of sextortionists
Publikationsdatum
01.12.2020
Erschienen in
Social Network Analysis and Mining / Ausgabe 1/2020
Print ISSN: 1869-5450
Elektronische ISSN: 1869-5469
DOI
https://doi.org/10.1007/s13278-020-00650-x

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