Achilles’ Heels: Vulnerable Record Identification in Synthetic Data Publishing

Author:

Meeus Matthieu,Guepin Florent,Creţu Ana-Maria,de Montjoye Yves-Alexandre

Publisher

Springer Nature Switzerland

Reference42 articles.

1. Alan Turing Institute: Resprosyn (2022). https://github.com/alan-turing-institute/reprosyn

2. Allard, T.: Snake challenge (2023). https://www.codabench.org/competitions/879/

3. Annamalai, M.S.M.S., Gadotti, A., Rocher, L.: A linear reconstruction approach for attribute inference attacks against synthetic data. arXiv preprint arXiv:2301.10053 (2023)

4. Bates, A., Spakulová, I., Dove, I., Mealor, A.: ONS methodology working paper series number 16-synthetic data pilot. https://www.ons.gov.uk/methodology/methodologicalpublications/generalmethodology/onsworkingpaperseries/onsmethodologyworkingpaperseriesnumber16syntheticdatapilot (2019), accessed on 02/06/2023

5. Bauer, L.A., Bindschaedler, V.: Towards realistic membership inferences: the case of survey data. In: Annual Computer Security Applications Conference, pp. 116–128 (2020)

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