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More Sparking Soundex-Based Privacy-Preserving Record Linkage

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Algorithmic Aspects of Cloud Computing (ALGOCLOUD 2022)

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Abstract

Privacy preserving record linkage refers to the problem of matching records from two or more data holders without revealing any personal identifiers, thus, maintaining the privacy of the individuals described by these records. While parallel processing has been deployed in the context of privacy preserving record linkage for handling big data, in this paper, we further explore parallel methods based on Apache Spark and phonetic codes and propose improvements, which manage to achieve superior performance with respect to time efficiency and privacy characteristics. To support our claims, we provide extensive experimental results and a rigorous discussion.

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Notes

  1. 1.

    https://okeanos-knossos.grnet.gr/home/.

  2. 2.

    Available at:https://github.com/datamechanics/delight.

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Authors and Affiliations

  1. Department of Applied Informatics, University of Macedonia, Thessaloniki, Greece

    Alexandros Karakasidis & Georgia Koloniari

Authors
  1. Alexandros Karakasidis
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  2. Georgia Koloniari
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Correspondence to Alexandros Karakasidis .

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Editors and Affiliations

  1. University of Bologna, Bologna, Italy

    Luca Foschini

  2. University of Patras, Rio, Greece

    Spyros Kontogiannis

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Karakasidis, A., Koloniari, G. (2023). More Sparking Soundex-Based Privacy-Preserving Record Linkage. In: Foschini, L., Kontogiannis, S. (eds) Algorithmic Aspects of Cloud Computing. ALGOCLOUD 2022. Lecture Notes in Computer Science, vol 13799. Springer, Cham. https://doi.org/10.1007/978-3-031-33437-5_5

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  • DOI: https://doi.org/10.1007/978-3-031-33437-5_5

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