Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/143527
Title: An ego network analysis of sextortionists
Authors: Oggier, Frederique
Datta, Anwitaman
Phetsouvanh, Silivanxay
Keywords: Science::Mathematics
Issue Date: 2020
Source: Oggier, F., Datta, A., & Phetsouvanh, S. (2020). An ego network analysis of sextortionists. Social Network Analysis and Mining, 10(1). doi:10.1007/s13278-020-00650-x
Journal: Social Network Analysis and Mining
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.
URI: https://hdl.handle.net/10356/143527
ISSN: 1869-5450
DOI: 10.1007/s13278-020-00650-x
DOI (Related Dataset): https://doi.org/10.21979/N9/VSK3KB
Schools: School of Computer Science and Engineering 
School of Physical and Mathematical Sciences 
Rights: © 2020 Springer. This is a post-peer-review, pre-copyedit version of an article published in Social Network Analysis and Mining. The final authenticated version is available online at: http://dx.doi.org/10.1007/s13278-020-00650-x
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SPMS Journal Articles

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