Scraping and Analyzing Data of a Large Darknet Marketplace

Authors

  • York Yannikos Fraunhofer Institute for Secure Information Technology SIT National Research Center for Applied Cybersecurity ATHENE Darmstadt, Germany
  • Julian Heeger Fraunhofer Institute for Secure Information Technology SIT National Research Center for Applied Cybersecurity ATHENE Darmstadt, Germany
  • Martin Steinebach Fraunhofer Institute for Secure Information Technology SIT National Research Center for Applied Cybersecurity ATHENE Darmstadt, Germany

DOI:

https://doi.org/10.13052/jcsm2245-1439.1222

Keywords:

darknet marketplaces, data acquisition, captcha solving, web crawling, convolutional neural networks

Abstract

Darknet marketplaces in the Tor network are popular places to anonymously buy and sell various kinds of illegal goods. Previous research on marketplaces ranged from analyses of type, availability and quality of goods to methods for identifying users. Although many darknet marketplaces exist, their lifespan is usually short, especially for very popular marketplaces that are in focus of law enforcement agencies.

We built a data acquisition architecture to collect data from White House Market, one of the largest darknet marketplaces in 2021. In this paper we describe our architecture and the problems we had to solve, and present findings from our analysis of the collected data.

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Author Biographies

York Yannikos, Fraunhofer Institute for Secure Information Technology SIT National Research Center for Applied Cybersecurity ATHENE Darmstadt, Germany

York Yannikos is a research associate in the Media Security and IT Forensics department at Fraunhofer SIT and a researcher at ATHENE. He holds a (equiv. Master’s) degree in computer science from the University of Rostock, Germany. His research interests include digital forensic tool testing, darknet marketplaces, and open source intelligence.

Julian Heeger, Fraunhofer Institute for Secure Information Technology SIT National Research Center for Applied Cybersecurity ATHENE Darmstadt, Germany

Julian Heeger is a research associate in the Media Security and IT Forensics department at Fraunhofer SIT and a researcher at ATHENE. He holds a Master’s degree in IT security from the Technical University of Darmstadt.

Martin Steinebach, Fraunhofer Institute for Secure Information Technology SIT National Research Center for Applied Cybersecurity ATHENE Darmstadt, Germany

Martin Steinebach is the head of the Media Security and IT Forensics department at Fraunhofer SIT. He studied computer science and received his PhD from the Technical University of Darmstadt for this work on digital audio watermarking in 2003. From 2003 to 2007 he was head of the Media Security in IT department at Fraunhofer IPSI. In 2016 he became honorary professor at the TU Darmstadt and gives lectures on multimedia security as well as civil security. He is principle investigator at ATHENE and represents IT Forensics and AI Security. Previously, he was principle investigator at CASED with the topics multimedia security and IT forensics.

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Published

2023-05-03

How to Cite

1.
Yannikos Y, Heeger J, Steinebach M. Scraping and Analyzing Data of a Large Darknet Marketplace. JCSANDM [Internet]. 2023 May 3 [cited 2024 Nov. 2];12(02):161-86. Available from: https://journals.riverpublishers.com/index.php/JCSANDM/article/view/19067

Issue

2023: Vol 12 Iss 2

Section

ARES 2022 Workshops

License

Copyright (c) 2023 Journal of Cyber Security and Mobility

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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

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