OSINT and human trafficking

  • Labour exploitation victims are often recruited through online job advertisements;
  • These advertisements are not only published on classified job websites but also posted and circulated on social media in specialised job searching groups and mutual aid groups as well as groups meant to foster information exchange among migrant workers;
  • There is evidence that commercial sex advertisements are mainly located on the surface and deep web, as opposed to the dark web, given the desire of commercial sex advertisers to reach the largest number of customers;
  • Online games are also used to approach potential victims;
  • Indicators specific to ICT-facilitated THB show clear limitations and must be used in conjunction with social network analysis and human assessment of the evidence.


Brewster, B.,Ingle, T., Rankin, G. (2014).  Crawling Open-Source Data for Indicators of Human Trafficking. 2014 IEEE/ACM 7th International Conference on Utility and Cloud Computing.

Meyer, L. F., & Shelley, L. I. (2020). Human Trafficking Network Investigations: The Role of Open Source Intelligence and Large-Scale Data Analytics in Investigating Organized Crime. International Journal on Criminology 7 (2).

Upadhayay, B., Lodhia, M.A.Z., Behzadan, V. (2020). Combating Human Trafficking via Automatic OSINT Collection, Validation and Fusion. SAIL Lab, University of New Haven.

Migration-Related Risks Caused by Misconceptions of Opportunities and Requirement

MIRROR has received funding from the European Union’s Horizon 2020 research and innovation action program under grant agreement No 832921.

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