Design of a Privacy-Preserving Data Platform for Collaboration Against Human Trafficking [article]

Darren Edge, Weiwei Yang, Kate Lytvynets, Harry Cook, Claire Galez-Davis, Hannah Darnton, Christopher M. White
2020 arXiv   pre-print
Case records on victims of human trafficking are highly sensitive, yet the ability to share such data is critical to evidence-based practice and policy development across government, business, and civil society. We present new methods to anonymize, publish, and explore such data, implemented as a pipeline generating three artifacts: (1) synthetic data mitigating the privacy risk that published attribute combinations might be linked to known individuals or groups; (2) aggregate data mitigating
more » ... e utility risk that synthetic data might misrepresent statistics needed for official reporting; and (3) visual analytics interfaces to both datasets mitigating the accessibility risk that privacy mechanisms or analysis tools might not be understandable and usable by all stakeholders. We present our work as a design study motivated by the goal of transforming how the world's largest database of identified victims is made available for global collaboration against human trafficking.
arXiv:2005.05688v2 fatcat:ep72y2ehnfdfdepffrlikfccaa