Jackson, J;
Mitra, R;
Francis, B;
Dove, I;
(2024)
Obtaining (ϵ,δ)-Differential Privacy Guarantees When Using a Poisson Mechanism to Synthesize Contingency Tables.
In: Domingo-Ferrer, J and Önen, M, (eds.)
Privacy in Statistical Databases. PSD 2024.
(pp. pp. 102-112).
Springer Nature: Cham, Switzerland.
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Abstract
We show that differential privacy type guarantees can be obtained when using a Poisson synthesis mechanism to protect counts in contingency tables. Specifically, we show how to obtain (ϵ,δ)-probabilistic differential privacy guarantees via the Poisson distribution’s cumulative distribution function. We demonstrate this empirically with the synthesis of an administrative-type confidential database.
| Type: | Proceedings paper |
|---|---|
| Title: | Obtaining (ϵ,δ)-Differential Privacy Guarantees When Using a Poisson Mechanism to Synthesize Contingency Tables |
| ISBN-13: | 9783031696503 |
| DOI: | 10.1007/978-3-031-69651-0_7 |
| Publisher version: | https://doi.org/10.1007/978-3-031-69651-0_7 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Statistical Science |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10201416 |
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