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A Survey on Privacy Preserving Synthetic Data Generation and a Discussion on a Privacy-Utility Trade-off Problem

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Science of Cyber Security - SciSec 2022 Workshops (SciSec 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1680))

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Abstract

Sharing microdata is a very important part of the present day world, but when they contain sensitive information, privacy to individuals needs to be guaranteed before release of data. One idea is to study the distributional properties of a data-set and generate synthetic data which has similar properties but unlike the original data comes with a privacy guarantee. In this review paper, we describe in detail, some advanced privacy guarantees that needs to be checked before release of such information. Also, we discuss some utility metrics to measure the remaining utility of released data. Very few mechanisms have been developed to ensure utility to synthetic data, provided a very strong privacy guarantee is maintained. We discuss some existing methodologies on privacy preserving synthetic data generation and discuss a privacy utility tradeoff problem.

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Acknowledgments

We are grateful to the reviewers of SciSec 2022 for their thorough proof-reading and valuable comments on our paper.

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Authors and Affiliations

  1. TCG CREST, Kolkata, India

    Debolina Ghatak

  2. Kyushu University, Fukuoka, Japan

    Kouichi Sakurai

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  1. Debolina Ghatak
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  2. Kouichi Sakurai
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Correspondence to Debolina Ghatak .

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Editors and Affiliations

  1. University of Aizu, Aizuwakamatsu, Fukushima, Japan

    Chunhua Su

  2. Kyushu University, Fukuoka, Fukuoka, Japan

    Kouichi Sakurai

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Ghatak, D., Sakurai, K. (2022). A Survey on Privacy Preserving Synthetic Data Generation and a Discussion on a Privacy-Utility Trade-off Problem. In: Su, C., Sakurai, K. (eds) Science of Cyber Security - SciSec 2022 Workshops. SciSec 2022. Communications in Computer and Information Science, vol 1680. Springer, Singapore. https://doi.org/10.1007/978-981-19-7769-5_13

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  • DOI: https://doi.org/10.1007/978-981-19-7769-5_13

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