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- W4313342281 endingPage "180" @default.
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- W4313342281 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." @default.
- W4313342281 created "2023-01-06" @default.
- W4313342281 creator A5001126368 @default.
- W4313342281 creator A5057451167 @default.
- W4313342281 date "2022-01-01" @default.
- W4313342281 modified "2023-10-12" @default.
- W4313342281 title "A Survey on Privacy Preserving Synthetic Data Generation and a Discussion on a Privacy-Utility Trade-off Problem" @default.
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- W4313342281 doi "https://doi.org/10.1007/978-981-19-7769-5_13" @default.
- W4313342281 hasPublicationYear "2022" @default.
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