Using Identification Codes in the Two-Party Privacy-Preserving Record Linkage (PPRL)

In this paper, we show the problem of two-party privacy-preserving record linkage (PPRL) can be seen as an identification problem in Information Theory. We propose to apply the identification codes that are designed for identification via channels to the problem of PPRL, due to their advantage in the performance analysis, especially on a quantitative evaluation of the privacy. Note that for the PPRL, linkage quality is typically evaluated experimentally, whilst for privacy, there are so far no commonly accepted privacy measures available that allow an objective evaluation. Our approach of identification code provides an objective evaluation on both linkage quality and privacy based on parameters of employed identification codes.

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Publication Details

Journal
JUCS - Journal of Universal Computer Science
Published
2025-08-12
DOI
https://doi.org/10.3897/jucs.167412
Primary Topic
Data Quality and Management
Type
article
Field-Weighted Citation Impact
0.00

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article

Using Identification Codes in the Two-Party Privacy-Preserving Record Linkage (PPRL)

Yanling Chen
JUCS - Journal of Universal Computer Science
Data Quality and Management
article

Using Identification Codes in the Two-Party Privacy-Preserving Record Linkage (PPRL)

Yanling Chen
article en

Abstract

In this paper, we show the problem of two-party privacy-preserving record linkage (PPRL) can be seen as an identification problem in Information Theory. We propose to apply the identification codes that are designed for identification via channels to the problem of PPRL, due to their advantage in the performance analysis, especially on a quantitative evaluation of the privacy. Note that for the PPRL, linkage quality is typically evaluated experimentally, whilst for privacy, there are so far no commonly accepted privacy measures available that allow an objective evaluation. Our approach of identification code provides an objective evaluation on both linkage quality and privacy based on parameters of employed identification codes.

JUCS - Journal of Universal Computer ScienceVol. 31(9)
Deutsche Forschungsgemeinschaft, Universität Duisburg-Essen
Peace, Justice and strong institutions
Openalex Percentile: Top 76%
Data Quality and Management
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Using Identification Codes in the Two-Party Privacy-Preserving Record Linkage (PPRL) — Yanling Chen · JUCS - Journal of Universal Computer Science (2025) | TGRS Research Map | TGRS