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Towards Privacy-Preserving Record Linkage with Record-Wise Linkage Policy

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Database and Expert Systems Applications (DEXA 2017)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10438))

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Abstract

We consider a situation that a large number of individuals contribute their personal data to multiple databases, and an analyst is allowed to issue a request of record linkage across any two of these databases. In such a situation, one concern is that very detailed information about individuals can be eventually obtained by analysts through sequential requests of record linkage across various database pairs. To resolve this privacy concern, we introduce a novel privacy notion for record linkage, record-wise linkage policy, with which each data contributor can individually designate database pairs that are allowed (resp. banned) to process record linkage by whitelist (resp. blacklist). We propose a secure multi-party computation to achieve record linkage with record-wise linkage policies. Also, we prove that our protocol can securely evaluate PPRL without violating given linkage policies and evaluate the efficiency of our protocol with experiments.

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Acknowledgement

This research was partly supported by the program “Research and Development on Real World Big Data Integration and Analysis” of the Ministry of Education, Culture, Sports, Science and Technology, Japan and RIKEN and JST CREST Grant Number JPMJCR1302, Japan.

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Authors and Affiliations

  1. University of Tsukuba, Ten’ nohdai 1-1-1, Tsukuba, Japan

    Takahito Kaiho, Wen-jie Lu, Toshiyuki Amagasa & Jun Sakuma

Authors
  1. Takahito Kaiho
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  2. Wen-jie Lu
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  3. Toshiyuki Amagasa
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  4. Jun Sakuma
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Corresponding author

Correspondence to Wen-jie Lu .

Editor information

Editors and Affiliations

  1. University of Lyon, Villeurbanne, France

    Djamal Benslimane

  2. University of Milan, Milan, Italy

    Ernesto Damiani

  3. University of Michigan, Dearborn, Michigan, USA

    William I. Grosky

  4. Paul Sabatier University, Toulouse, France

    Abdelkader Hameurlain

  5. Wright State University, Dayton, Ohio, USA

    Amit Sheth

  6. Johannes Kepler University, Linz, Austria

    Roland R. Wagner

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Kaiho, T., Lu, Wj., Amagasa, T., Sakuma, J. (2017). Towards Privacy-Preserving Record Linkage with Record-Wise Linkage Policy. In: Benslimane, D., Damiani, E., Grosky, W., Hameurlain, A., Sheth, A., Wagner, R. (eds) Database and Expert Systems Applications. DEXA 2017. Lecture Notes in Computer Science(), vol 10438. Springer, Cham. https://doi.org/10.1007/978-3-319-64468-4_18

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  • DOI: https://doi.org/10.1007/978-3-319-64468-4_18

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-64467-7

  • Online ISBN: 978-3-319-64468-4

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