A Depiction and Classification of the Stolen Data Market Ecosystem and Comprising Darknet Markets: A Multidisciplinary Approach

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 adve...

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Bibliographic Details
Main Author: Howell, C. Jordan (Author)
Contributors: Fisher, Taylor ; Muniz, Caitlyn N. ; Maimon, David ; Rotzinger, Yolanda
Format: Electronic Article
Language:English
Published: 2023
In: Journal of contemporary criminal justice
Year: 2023, Volume: 39, Issue: 2, Pages: 298-317
Online Access: Volltext (lizenzpflichtig)
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Keywords:
Cybercrime
Cybersecurity
Darkweb
business ecosystem
stolen data
Description
Summary: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.
ISSN:1552-5406
DOI:10.1177/10439862231158005