Uniqueness Ratio as a Predictor of a Privacy Leakage

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OpenAlexPublished 2026Artificial Intelligence & Computer ScienceArtificial Intelligence
Journal
Zenodo (CERN European Organization for Nuclear Research)
Publisher
European Organization for Nuclear Research
Record source
OpenAlex Research Library

Abstract / Description

This paper introduces Uniqueness Ratio as a pre-join metric for predicting privacy leakage in integrated databases. It analyzes how attribute combinations become identifying only after dataset joins, enabling early risk assessment before data integration using machine learning.
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