Synthetic Data, Similarity-based Privacy Metrics, and Regulatory (Non-)Compliance
Abstract
In this paper, we argue that similarity-based privacy metrics cannot ensure regulatory compliance of synthetic data. Our analysis and counter-examples show that they do not protect against singling out and linkability and, among other fundamental issues, completely ignore the motivated intruder test.
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