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Non-traditional cyber adversaries: Combatting human trafficking through data science

Author

Listed:
  • Borrelli, Danielle

    (California Cybersecurity Institute and Program Lead, Trafficking Investigations Hub, USA)

  • Caltagirone, Sherrie

    (Founder and Executive Director, Global Emancipation Network, USA)

Abstract

Human trafficking is a complex and challenging global crime exacerbated by the use of technology. This paper begins by dicussing how traffickers utilise technology for scalability, anonymity and profitability as the Internet, social media platforms and encrypted messaging make the recruitment, exploitation and profit of an individual a low-risk, high-reward enterprise. It goes on to describe how counter-trafficking efforts are often siloed approaches, resulting in decentralised information and analysis on the size and scope of trafficking in persons. It presents resources and tools such as the human trafficking kill chain methodology and Artemis, a machine learning (ML) human trafficking risk classifier, show promising disruption tactics which may also be applied to other asymmetrical threats. Recommendations for centralised data collections methods, interagency collaboration and cybersecurity adjacent legislation are also made.

Suggested Citation

  • Borrelli, Danielle & Caltagirone, Sherrie, 2020. "Non-traditional cyber adversaries: Combatting human trafficking through data science," Cyber Security: A Peer-Reviewed Journal, Henry Stewart Publications, vol. 4(1), pages 77-90, September.
    • Handle: RePEc:aza:csj000:y:2020:v:4:i:1:p:77-90
    as

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    More about this item

    Keywords

    trafficking; sexual exploitation; cyber; adversaries; data;
    All these keywords.

    JEL classification:

    • M15 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - IT Management

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