Examining the Uncharted Dark Web

Trust Signalling on Single Vendor Shops

Dados Bibliográficos

ID2153544
AutoresDominique Laferrière (École de criminologie, Université de Montréal, Montréal, Canada, autor correspondente), David Décary-Hétu (0000-0002-4360-140X, École de criminologie, Université de Montréal, Montréal, Canada)
Ano2023
Volume44
Fascículo1
Páginas37-56
Data de publicação2023-01-02
Peer ReviewedSim
Open AccessNão
TipoARTICLE
PeriódicoDeviant Behavior (JOURNAL)
Identificadores do periódicoISSN: 0163-9625 • E-ISSN: 1521-0456
EditoraInforma UK Limited (PUBLISHER • GB)
DOI10.1080/01639625.2021.2011479
OpenAlexW4210594519
IdiomaEN
Citações recebidas11
Referências citadas36

Despite their growing popularity, cryptomarkets generate risks for participants. This has promoted the reemergence of a more personal transaction model on the dark web: single vendor shops. To date, little is known about how single vendors display trust to attract potential customers without relying on the structural trust provided by cryptomarkets' review and escrow systems. A total of 108 single vendor shops were identified. A coding grid was used to determine whether vendors displayed any of the four categories of trust signals typically found on cryptomarkets (i.e., signals related to identity, marketing, security, and signals that directly express trust). While the majority of single vendor shops were involved in illicit drug dealing, other products such as electronics, weapons, and fake documents were also offered. On average, shops displayed few trust signals. However, variations between different kinds of vendors were found: while vendors involved in illicit drug dealing displayed more identity- and marketing-related trust signals, vendors involved in fraud displayed more security-related signals and signals that directly expressed trust. Differences between vendors might be due to the nature of the products they offer and to the level of competition in their respective markets

Advertising · Business · Computer security · Database transaction · Identity Theft · Information leakage · Internet privacy · Popularity · Vendor · Computer Science · Crime, Illicit Activities, and Governance · Cybercrime and Law Enforcement Studies · Spam and Phishing Detection · Marketing