Wang, Yichao, Arief, Budi, Hernandez-Castro, Julio C. (2021) Toad in the Hole or Mapo Tofu? Comparative Analysis of English and Chinese Darknet Markets. In: 2021 APWG Symposium on Electronic Crime Research (eCrime). . pp. 1-13. IEEE ISBN 978-1-66548-029-1. (doi:10.1109/eCrime54498.2021.9738745) (KAR id:99679)
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Official URL: https://doi.org/10.1109/eCrime54498.2021.9738745 |
Abstract
The popularity of online shopping and cryptocurrency has contributed to drive the economy of darknet markets in recent years. These are often perceived to be conducive to (or may even facilitate) cybercrime related activities. It is, therefore, worthwhile to have a deeper understanding of how various darknet markets operate, so that researchers and law enforcement agencies can test and deploy appropriate countermeasures to fight against online crime. Currently, there is a knowledge gap regarding the similarities and differences among darknet markets in different languages. This study aims to compare between darknet markets operating in English and Chinese. Data from three English and two Chinese darknet markets was collected. The gathered data is described, compared, and analysed in six main aspects: operation model and structures, product categories, market policies, payment methods, security mechanisms, and vendors' characteristics. Our datasets were collected during a seven-week period between 17 July and 30 August 2021, and they contain data from 384 vendors in the English darknet markets and 4,429 in the Chinese ones. The Chinese darknet markets generally seem to have more liberal policies than their English counterparts, as demonstrated by the variety and types of goods and services offered, many of which would have been banned in the English speaking ones. All darknet markets suffer from reputation issues. Cross-market actors are active, but they represent only a small proportion of the vendors observed in our study. In summary, our findings reveal key characteristics of darknet markets in two widely used languages. This information can provide useful insights for security researchers and law enforcement agencies in combating cybercrime.
Item Type: | Conference or workshop item (Proceeding) |
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DOI/Identification number: | 10.1109/eCrime54498.2021.9738745 |
Subjects: | Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming, |
Divisions: |
Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing University-wide institutes > Institute of Cyber Security for Society |
Funders: | University of Kent (https://ror.org/00xkeyj56) |
Depositing User: | Yichao Wang |
Date Deposited: | 24 Jan 2023 22:04 UTC |
Last Modified: | 25 Jan 2023 17:08 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/99679 (The current URI for this page, for reference purposes) |
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