RT Article
T1 A Depiction and Classification of the Stolen Data Market Ecosystem and Comprising Darknet Markets: A Multidisciplinary Approach
JF Journal of contemporary criminal justice
VO 39
IS 2
SP 298
OP 317
A1 Howell, C. Jordan
A2 Fisher, Taylor
A2 Muniz, Caitlyn N.
A2 Maimon, David 1978-
A2 Rotzinger, Yolanda
LA English
YR 2023
UL https://krimdok.uni-tuebingen.de/Record/1844737403
AB Scant research has investigated the illicit online ecosystem that enables the sale of stolen data. Even fewer studies have examined the longitudinal trends of the markets on which these data are bought and sold. To fill this gap in the literature, our research team identified 30 darknet markets advertising stolen data products from September 1, 2020, through April 30, 2021. We then developed python web scrapers to systematically extract information pertaining to stolen data products on a weekly basis. Using these data, we calculated the number of vendors, listings, sales, and revenue across the markets and at the aggregate, ecosystem level. Moreover, we developed a data-driven market classification system drawing from ecological principles and dominant firm theory. Findings indicate that markets vary in size and success. Although some markets generated over $91 million in revenue from stolen data products, the median revenue across markets during the observational period was only $95,509. Variability also exists across markets in respect to the number of vendors, listings, and sales. Only three markets were classified as financially successful and stable (i.e., dominant firms). We argue resources should be allocated to target markets fitting these criteria.
K1 stolen data
K1 Darkweb
K1 Cybersecurity
K1 Cybercrime
K1 business ecosystem
DO 10.1177/10439862231158005