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Design of a Privacy-Preserving Data Platform for Collaboration Against Human Trafficking
[article]
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
arXiv:2005.05688v2
fatcat:ep72y2ehnfdfdepffrlikfccaa