Publikationen

Autor	Yannikos, York; Heeger, Julian; Steinebach, Martin
Datum	2023
Art	Journal Article
Abstrakt	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.
Konferenz	International Conference on Availability, Reliability and Security 2022
Url	https://publica.fraunhofer.de/handle/publica/441382

Scraping and Analyzing Data of a Large Darknet Marketplace