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

• Author: C. Jordan Howell,Taylor Fisher,Caitlyn N. Muniz,David Maimon,Yolanda Rotzinger
• DOI: http://doi.org/10.1177/10439862231158005
• Published date: 01 May 2023
• Date: 01 May 2023
• Subject Matter: Articles

https://doi.org/10.1177/10439862231158005

Journal of Contemporary Criminal Justice

2023, Vol. 39(2) 298 –317

© The Author(s) 2023

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DOI: 10.1177/10439862231158005

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Article

A Depiction and

Classification of the Stolen

Data Market Ecosystem

and Comprising Darknet

Markets: A Multidisciplinary

Approach

C. Jordan Howell1, Taylor Fisher2,

Caitlyn N. Muniz3, David Maimon4, and

Yolanda Rotzinger3

Abstract

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

1University of South Florida, Sarasota, USA

2University of South Florida, Tampa, USA

3The University of Texas at El Paso, USA

4Georgia State University, Atlanta, USA

Corresponding Author:

Taylor Fisher, Department of Criminology, University of South Florida, 4202 E. Fowler Ave., Tampa, FL

33620-8100, USA.

Email: tsfisher1@usf.edu

1158005CCJXXX10.1177/10439862231158005Journal of Contemporary Criminal JusticeHowell et al.

research-article2023

Howell et al. 299

and stable (i.e., dominant firms). We argue resources should be allocated to target

markets fitting these criteria.

Keywords

business ecosystem, cybercrime, cybersecurity, darkweb, stolen data

Introduction

Darknet markets, like traditional e-commerce sites and brick and mortar shops, are a

space for vendors to connect with potential buyers to facilitate transactions (Wall,

2007), both licit and illicit. Although vendors on the darknet advertise a host of legal

commodities, these markets are notorious for the sale of various illegal products such

as drugs (Christin & Thomas, 2019), guns (Holt & Lee, 2022), and stolen data (Ouellet

et al., 2022). The first modern darknet market, Silk Road, was operational from 2011

to 2013. Since the market’s seizure, myriad markets have emerged to fill the void

(Décary-Hétu & Giommoni, 2017; Ladegaard, 2019, 2020; Norbutas et al., 2020;

Soska & Christin, 2015; Van Buskirk et al., 2017). These markets now function as a

complex interconnected network (Ouellet et al., 2022) resembling what Moore (1993)

referred to as a “business ecosystem.”

In the natural sciences, such as ecology and geography, ecosystems are defined as

a community of interacting organisms and their physical environment. Ecosystems

consist of a combination of biotic (living) and abiotic (non-living) components that

interact to form a complex interconnected network. Ecologists have long recognized

the interdependence of organisms and the importance of this connection for evolution

and survival. Scholars from across academic disciplines are now applying ecological

principles to explain interconnectivity and coevolution in non-biological ecosystems.

For example, in a business ecosystem, members coevolve through cooperative, yet

competitive, innovation (Moore, 1993). Using ecological metaphors, Moore (1993)

depicted a cohesive network of companies whose survival and anticipated profits are

contingent on interconnectivity. From an ecological perspective, it does not matter

which businesses survive within the ecosystem if “competition among them is fierce

and fair” (Moore, 1993, p. 86). Some companies, however, become dominant and

disproportionately influence the ecosystem’s evolution. These “dominant firms,” or

oligopolies, have significantly more market shares than their rivals because they are

more stable and generate more revenue than their competition (Forchheimer, 1908;

Stigler, 1937). A dominant firm often has some competitive advantage (e.g., lower

costs, better reputation) that allows them to maintain their position within the business

ecosystem (Gilbert, 1978). Fringe firms, however, are peripheral to the network and

their survival is of lesser (or no) concern. Classifying companies as “dominant” or

“fringe” helps shape our understanding of the power dynamics within the ecosystem

and determine which markets are essential for survival (Forchheimer, 1908).