Early warning signals for predicting cryptomarket vendor success using dark net forum networks

arXiv (Cornell University)

Abstract

In this work we focus on identifying key players in dark net cryptomarkets that facilitate online trade of illegal goods. Law enforcement aims to disrupt criminal activity conducted through these markets by targeting key players vital to the market's existence and success. We particularly focus on detecting successful vendors responsible for the majority of illegal trade. Our methodology aims to uncover whether the task of key player identification should center around plainly measuring user and forum activity, or that it requires leveraging specific patterns of user communication. We focus on a large-scale dataset from the Evolution cryptomarket, which we model as an evolving communication network. Results indicate that user and forum activity, measured through topic engagement, is best able to identify successful vendors. Interestingly, considering users with higher betweenness centrality in the communication network further improves performance, also identifying successful vendors with moderate activity on the forum. But more importantly, analyzing the forum data over time, we find evidence that attaining a high betweenness score comes before vendor success. This suggests that the proposed network-driven approach of modelling user communication might prove useful as an early warning signal for key player identification.

Authors 3

1. Hanjo D. Boekhout Aachen Institute of Advanced Computer Science

   Leiden University

   Affiliation as printed

   Leiden University , Institute of Advanced Computer Science , Niels Bohrweg 1 , 2333 CA Leiden , Netherlands

2. ARJAN A. J. BLOKLAND Aachen Institute of Criminal Law and Criminology

   Leiden University · Netherlands Institute for the Study of Crime and Law Enforcement

   Affiliation as printed

   Leiden University , Institute of Criminal Law and Criminology , Steenschuur 25 , 2311 ES Leiden , Netherlands

   Netherlands Institute for the Study of Crime and Law Enforcement (NCSR) , De Boelelaan 1077 , 1081 HV Amsterdam , Netherlands

3. Frank W. Takes Aachen Institute of Advanced Computer Science

   Leiden University

   Affiliation as printed

   Leiden University , Institute of Advanced Computer Science , Niels Bohrweg 1 , 2333 CA Leiden , Netherlands