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Data Privacy for Record Linkage and Beyond

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  • Shurong Lin
  • Eric Kolaczyk

Abstract

In a data-driven world, two prominent research problems are record linkage and data privacy, among others. Record linkage is essential for improving decision-making by integrating information of the same entities from different sources. On the other hand, data privacy research seeks to balance the need to extract accurate insights from data with the imperative to protect the privacy of the entities involved. Inevitably, data privacy issues arise in the context of record linkage. This article identifies two complementary aspects at the intersection of these two fields: (1) how to ensure privacy during record linkage and (2) how to mitigate privacy risks when releasing the analysis results after record linkage. We specifically discuss privacy-preserving record linkage, differentially private regression, and related topics.

Suggested Citation

  • Shurong Lin & Eric Kolaczyk, 2024. "Data Privacy for Record Linkage and Beyond," NBER Working Papers 32940, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:32940
    Note: TWP
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    JEL classification:

    • C0 - Mathematical and Quantitative Methods - - General

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