The Network of Online Stolen Data Markets
How Vendor Flows Connect Digital Marketplaces
Bibliographic Data
| ID | 8401753 |
|---|---|
| Authors | M Ouellet (0000-0003-4442-3374, Georgia State University, corresponding author), David Maimon (0000-0003-1492-2762, Georgia State University), Jordan C Howell (The University of Texas at El Paso), Yubao Wu (0000-0001-9356-8508, Georgia State University) |
| Year | 2022 |
| Volume | 62 |
| Issue | 6 |
| Pages | 1518-1536 |
| Publication date | 2022-10-13 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | The British Journal of Criminology (JOURNAL) |
| Journal identifiers | ISSN: 0007-0955 • E-ISSN: 1464-3529 |
| Publisher | Oxford University Press (PUBLISHER • GB) |
| DOI | 10.1093/bjc/azab116 |
| OpenAlex | W4226054751 |
| Language | EN |
| Citations received | 11 |
| References cited | 42 |
In the face of market uncertainty, illicit actors on the darkweb mitigate risk by displacing their operations across digital marketplaces. In this study, we reconstruct market networks created by vendor displacement to examine how digital marketplaces are connected on the darkweb and identify the properties that drive vendor flows before and after a law enforcement disruption. Findings show that vendors’ movement across digital marketplaces creates a highly connected ecosystem; nearly all markets are directly or indirectly connected. These network characteristics remain stable following a law enforcement operation; prior vendor flows predict vendor movement before and after the interdiction. The findings inform work on collective patterns in offender decision-making and extend discussions of displacement into digital spaces
Business · Computer security · Enforcement · Interdiction · Law enforcement · Vendor · Work (physics) · Computer Science · Crime Patterns and Interventions · Crime, Illicit Activities, and Governance · Cybercrime and Law Enforcement Studies · Engineering · Law · Marketing
Risk Avoidance Behavior on Darknet Marketplaces
When the Markets Are Inaccessible
Stolen data markets on Telegram
Follow the Money
A Depiction and Classification of the Stolen Data Market Ecosystem and Comprising Darknet Markets
Understanding the Mechanisms that Drive Relational Events Dynamics and Structure in Corruption Networks
Dude, Where’s My Check? An Osint-Based Analysis of the Link Between Check Theft and Identity Theft
How cryptomarket communities navigate marketplace structures, risk perceptions and ideologies amid evolving cryptocurrency practices
Hydra
The structure of cooperation among organized crime groups
Crime and Calculation
Social Network Analysis
Crime and Nature
Do police crackdowns disrupt drug cryptomarkets? A longitudinal analysis of the effects of Operation Onymous
Silk Road: Ebay for Drugs
Exponential-family random graph models for valued networks
Hot spots policing and crime reduction
Social Learning and Social Structure
A Reconceptualization of General and Specific Deterrence
Social Learning Theory of Aggression
Crime Prevention and the Displacement Phenomenon
Open Secrecy
We Know Where You Are, What You Are Doing and We Will Catch You
Centrality in social networks conceptual clarification
Building them up, breaking them down
The efficiency/security trade-off in criminal networks
Criminal collaboration and risk
Reputation transferability across contexts
Hidden wholesale
Delivery dilemmas
Crime displacement in digital drug markets
Risks and Prices
Companions in Crime
Examining the displacement practices of johns with on-line data
Crime and Punishment
Incentives for Collective Deviance
Does Crime Just Move Around the Corner? A Controlled Study of Spatial Displacement and Diffusion of Crime Control Benefits
Mentors and Criminal Achievement
Cybercriminal Networks, Social Ties and Online Forums
Co-offending as Social Exchange. Explaining Characteristics of Co-offending
A Crime Script Analysis of the Online Stolen Data Market
Selling Drugs on Darkweb Cryptomarkets
Exponential Random Graph Models for Social Networks
Statistical Network Analysis for Analyzing Policy Networks
Reputation Formation and the Evolution of Cooperation in Anonymous Online Markets
Flow My FE the Vendor Said
| Citations per year | 3.67 |
|---|---|
| Citation span | 2023 - 2026 (4) |
| Highly cited | No |