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An ego network analysis of sextortionists

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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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  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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Correspondence to Anwitaman Datta.

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See Tables 4 and 5.

Table 4 List of Bitcoin addresses referred in this paper using the first five symbols
Table 5 List of transaction hashes referred in this paper using the first five symbols

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Oggier, F., Datta, A. & Phetsouvanh, S. An ego network analysis of sextortionists. Soc. Netw. Anal. Min. 10, 44 (2020).

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