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Optimal Membership Inference Bounds for Adaptive Composition of Sampled
  Gaussian Mechanisms

Optimal Membership Inference Bounds for Adaptive Composition of Sampled Gaussian Mechanisms

12 April 2022
Saeed Mahloujifar
Alexandre Sablayrolles
Graham Cormode
S. Jha
ArXivPDFHTML

Papers citing "Optimal Membership Inference Bounds for Adaptive Composition of Sampled Gaussian Mechanisms"

11 / 11 papers shown
Title
Closed-Form Bounds for DP-SGD against Record-level Inference
Closed-Form Bounds for DP-SGD against Record-level Inference
Giovanni Cherubin
Boris Köpf
Andrew J. Paverd
Shruti Tople
Lukas Wutschitz
Santiago Zanella Béguelin
46
2
0
22 Feb 2024
Gradients Look Alike: Sensitivity is Often Overestimated in DP-SGD
Gradients Look Alike: Sensitivity is Often Overestimated in DP-SGD
Anvith Thudi
Hengrui Jia
Casey Meehan
Ilia Shumailov
Nicolas Papernot
33
3
0
01 Jul 2023
On the Query Complexity of Training Data Reconstruction in Private
  Learning
On the Query Complexity of Training Data Reconstruction in Private Learning
Prateeti Mukherjee
Satyanarayana V. Lokam
35
0
0
29 Mar 2023
Bounding Training Data Reconstruction in DP-SGD
Bounding Training Data Reconstruction in DP-SGD
Jamie Hayes
Saeed Mahloujifar
Borja Balle
AAML
FedML
33
39
0
14 Feb 2023
Privacy Risk for anisotropic Langevin dynamics using relative entropy
  bounds
Privacy Risk for anisotropic Langevin dynamics using relative entropy bounds
Anastasia Borovykh
N. Kantas
P. Parpas
G. Pavliotis
19
1
0
01 Feb 2023
Analyzing Privacy Leakage in Machine Learning via Multiple Hypothesis
  Testing: A Lesson From Fano
Analyzing Privacy Leakage in Machine Learning via Multiple Hypothesis Testing: A Lesson From Fano
Chuan Guo
Alexandre Sablayrolles
Maziar Sanjabi
FedML
29
17
0
24 Oct 2022
Generalised Likelihood Ratio Testing Adversaries through the
  Differential Privacy Lens
Generalised Likelihood Ratio Testing Adversaries through the Differential Privacy Lens
Georgios Kaissis
Alexander Ziller
Stefan Kolek Martinez de Azagra
Daniel Rueckert
12
0
0
24 Oct 2022
CANIFE: Crafting Canaries for Empirical Privacy Measurement in Federated
  Learning
CANIFE: Crafting Canaries for Empirical Privacy Measurement in Federated Learning
Samuel Maddock
Alexandre Sablayrolles
Pierre Stock
FedML
20
22
0
06 Oct 2022
Measuring Forgetting of Memorized Training Examples
Measuring Forgetting of Memorized Training Examples
Matthew Jagielski
Om Thakkar
Florian Tramèr
Daphne Ippolito
Katherine Lee
...
Eric Wallace
Shuang Song
Abhradeep Thakurta
Nicolas Papernot
Chiyuan Zhang
TDI
73
102
0
30 Jun 2022
Bounding Membership Inference
Bounding Membership Inference
Anvith Thudi
Ilia Shumailov
Franziska Boenisch
Nicolas Papernot
33
18
0
24 Feb 2022
Extracting Training Data from Large Language Models
Extracting Training Data from Large Language Models
Nicholas Carlini
Florian Tramèr
Eric Wallace
Matthew Jagielski
Ariel Herbert-Voss
...
Tom B. Brown
D. Song
Ulfar Erlingsson
Alina Oprea
Colin Raffel
MLAU
SILM
290
1,824
0
14 Dec 2020
1