Evaluating Identity Disclosure Risk in Fully Synthetic Health Data: Model Development and Validation
Journal of Medical Internet Research2020Vol. 22(11), pp. e23139–e23139
Citations Over TimeTop 10% of 2020 papers
Abstract
We have presented a comprehensive identity disclosure risk model for fully synthetic data. The results for this synthesis method on 2 datasets demonstrate that synthesis can reduce meaningful identity disclosure risks considerably. The risk model can be applied in the future to evaluate the privacy of fully synthetic data.
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