You are your photographs: Detecting multiple identities of vendors in the darknet marketplaces

Xiangwen Wang, Peng Peng, Chun Wang, Gang Wang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Darknet markets are online services behind Tor where cybercriminals trade illegal goods and stolen datasets. In recent years, security analysts and law enforcement start to investigate the darknet markets to study the cybercriminal networks and predict future incidents. However, vendors in these markets often create multiple accounts (i.e., Sybils), making it challenging to infer the relationships between cybercriminals and identify coordinated crimes. In this paper, we present a novel approach to link the multiple accounts of the same darknet vendors through photo analytics. The core idea is that darknet vendors often have to take their own product photos to prove the possession of the illegal goods, which can reveal their distinct photography styles. To fingerprint vendors, we construct a series deep neural networks to model the photography styles. We apply transfer learning to the model training, which allows us to accurately fingerprint vendors with a limited number of photos. We evaluate the system using real-world datasets from 3 large darknet markets (7,641 vendors and 197,682 product photos). A ground-truth evaluation shows that the system achieves an accuracy of 97.5%, outperforming existing stylometry-based methods in both accuracy and coverage. In addition, our system identifies previously unknown Sybil accounts within the same markets (23) and across different markets (715 pairs). Further case studies reveal new insights into the coordinated Sybil activities such as price manipulation, buyer scam, and product stocking and reselling.

Original languageEnglish (US)
Title of host publicationASIACCS 2018 - Proceedings of the 2018 ACM Asia Conference on Computer and Communications Security
PublisherAssociation for Computing Machinery, Inc
Pages431-442
Number of pages12
ISBN (Electronic)9781450355766
DOIs
StatePublished - May 29 2018
Externally publishedYes
Event13th ACM Symposium on Information, Computer and Communications Security, ASIACCS 2018 - Incheon, Korea, Republic of
Duration: Jun 4 2018Jun 8 2018

Publication series

NameASIACCS 2018 - Proceedings of the 2018 ACM Asia Conference on Computer and Communications Security

Conference

Conference13th ACM Symposium on Information, Computer and Communications Security, ASIACCS 2018
CountryKorea, Republic of
CityIncheon
Period6/4/186/8/18

Keywords

  • Darknet Market
  • Image Analysis
  • Stylometry
  • Sybil Detection

ASJC Scopus subject areas

  • Software
  • Computer Science Applications
  • Information Systems
  • Computer Networks and Communications

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