Uniqueness Ratio as a Predictor of a Privacy Leakage
Abstract
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.
Fields of Study & Subjects
Information and Cyber Security
Privacy-Preserving Technologies in Data
Network Security and Intrusion Detection
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 12 December 2026
- Language
- EN