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CoK: A Survey of Privacy Challenges in Relation to Data Meshes

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Database and Expert Systems Applications (DEXA 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13426))

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Abstract

The growing volumes of data that appear on multiple distributed platforms raise the question of how to compose data meshes that can be published and/or shared safely amongst multiple cooperating parties. Data meshes are composed of subsets (or whole sets) of data repositories that are owned by autonomous parties. This raises new challenges in terms of guaranteeing privacy across various data mesh compositions. In this paper, we present a survey of the issues that emerge in guaranteeing the privacy of distributed mesh data. We discuss the limitations of existing solutions in handling personal data privacy with respect to meshed data. Finally, we postulate that identifying personal data in such datasets must be handled with a performance efficient algorithm that can determine (on-the-fly), potential linkages across various data repositories, that could be exploited to subvert privacy.

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Notes

  1. 1.

    https://github.com/jaSunny/synthetic_genome_data.

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Authors and Affiliations

  1. Hasso Plattner Institute, University of Potsdam, Potsdam, Germany

    Nikolai J. Podlesny, Anne V. D. M. Kayem & Christoph Meinel

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  1. Nikolai J. Podlesny
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  2. Anne V. D. M. Kayem
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  3. Christoph Meinel
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Correspondence to Nikolai J. Podlesny .

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Editors and Affiliations

  1. University of Vienna, Vienna, Austria

    Christine Strauss

  2. University of Calabria, Rende, Italy

    Alfredo Cuzzocrea

  3. Johannes Kepler University of Linz, Linz, Austria

    Gabriele Kotsis

  4. Vienna University of Technology, Vienna, Austria

    A Min Tjoa

  5. Johannes Kepler University of Linz, Linz, Austria

    Ismail Khalil

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Podlesny, N.J., Kayem, A.V.D.M., Meinel, C. (2022). CoK: A Survey of Privacy Challenges in Relation to Data Meshes. In: Strauss, C., Cuzzocrea, A., Kotsis, G., Tjoa, A.M., Khalil, I. (eds) Database and Expert Systems Applications. DEXA 2022. Lecture Notes in Computer Science, vol 13426. Springer, Cham. https://doi.org/10.1007/978-3-031-12423-5_7

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