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2307.01701
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Synthetic is all you need: removing the auxiliary data assumption for membership inference attacks against synthetic data
4 July 2023
Florent Guépin
Matthieu Meeus
Ana-Maria Cretu
Yves-Alexandre de Montjoye
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Papers citing
"Synthetic is all you need: removing the auxiliary data assumption for membership inference attacks against synthetic data"
8 / 8 papers shown
Title
The DCR Delusion: Measuring the Privacy Risk of Synthetic Data
Zexi Yao
Natasa Krco
Georgi Ganev
Yves-Alexandre de Montjoye
84
0
0
02 May 2025
Generating Synthetic Data with Formal Privacy Guarantees: State of the Art and the Road Ahead
Viktor Schlegel
Anil A Bharath
Zilong Zhao
Kevin Yee
66
0
0
26 Mar 2025
Synthetic Data Can Mislead Evaluations: Membership Inference as Machine Text Detection
Ali Naseh
Niloofar Mireshghallah
51
0
0
20 Jan 2025
Privacy Vulnerabilities in Marginals-based Synthetic Data
Steven Golob
Sikha Pentyala
Anuar Maratkhan
Martine De Cock
19
3
0
07 Oct 2024
A Zero Auxiliary Knowledge Membership Inference Attack on Aggregate Location Data
Vincent Guan
Florent Guépin
Ana-Maria Cretu
Yves-Alexandre de Montjoye
21
1
0
26 Jun 2024
"What do you want from theory alone?" Experimenting with Tight Auditing of Differentially Private Synthetic Data Generation
Meenatchi Sundaram Muthu Selva Annamalai
Georgi Ganev
Emiliano De Cristofaro
35
9
0
16 May 2024
VFLGAN: Vertical Federated Learning-based Generative Adversarial Network for Vertically Partitioned Data Publication
Xun Yuan
Yang Yang
P. Gope
A. Pasikhani
Biplab Sikdar
27
2
0
15 Apr 2024
Achilles' Heels: Vulnerable Record Identification in Synthetic Data Publishing
Matthieu Meeus
Florent Guépin
Ana-Maria Cretu
Yves-Alexandre de Montjoye
52
23
0
17 Jun 2023
1