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Defending against Reconstruction Attacks with Rényi Differential
  Privacy

Defending against Reconstruction Attacks with Rényi Differential Privacy

15 February 2022
Pierre Stock
I. Shilov
Ilya Mironov
Alexandre Sablayrolles
    AAML
    SILM
    MIACV
ArXivPDFHTML

Papers citing "Defending against Reconstruction Attacks with Rényi Differential Privacy"

15 / 15 papers shown
Title
DeSIA: Attribute Inference Attacks Against Limited Fixed Aggregate Statistics
DeSIA: Attribute Inference Attacks Against Limited Fixed Aggregate Statistics
Yifeng Mao
Bozhidar Stevanoski
Yves-Alexandre de Montjoye
49
0
0
25 Apr 2025
The Canary's Echo: Auditing Privacy Risks of LLM-Generated Synthetic Text
The Canary's Echo: Auditing Privacy Risks of LLM-Generated Synthetic Text
Matthieu Meeus
Lukas Wutschitz
Santiago Zanella Béguelin
Shruti Tople
Reza Shokri
80
0
0
24 Feb 2025
Recite, Reconstruct, Recollect: Memorization in LMs as a Multifaceted Phenomenon
Recite, Reconstruct, Recollect: Memorization in LMs as a Multifaceted Phenomenon
USVSN Sai Prashanth
Alvin Deng
Kyle O'Brien
Jyothir S V
Mohammad Aflah Khan
...
Jacob Ray Fuehne
Stella Biderman
Tracy Ke
Katherine Lee
Naomi Saphra
60
12
0
25 Jun 2024
Visual Privacy Auditing with Diffusion Models
Visual Privacy Auditing with Diffusion Models
Kristian Schwethelm
Johannes Kaiser
Moritz Knolle
Daniel Rueckert
Daniel Rueckert
Alexander Ziller
DiffM
AAML
35
0
0
12 Mar 2024
Data Reconstruction Attacks and Defenses: A Systematic Evaluation
Data Reconstruction Attacks and Defenses: A Systematic Evaluation
Sheng Liu
Zihan Wang
Yuxiao Chen
Qi Lei
AAML
MIACV
61
4
0
13 Feb 2024
A Note On Interpreting Canary Exposure
A Note On Interpreting Canary Exposure
Matthew Jagielski
20
4
0
31 May 2023
How to DP-fy ML: A Practical Guide to Machine Learning with Differential
  Privacy
How to DP-fy ML: A Practical Guide to Machine Learning with Differential Privacy
Natalia Ponomareva
Hussein Hazimeh
Alexey Kurakin
Zheng Xu
Carson E. Denison
H. B. McMahan
Sergei Vassilvitskii
Steve Chien
Abhradeep Thakurta
94
167
0
01 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-Aware Compression for Federated Learning Through Numerical
  Mechanism Design
Privacy-Aware Compression for Federated Learning Through Numerical Mechanism Design
Chuan Guo
Kamalika Chaudhuri
Pierre Stock
Michael G. Rabbat
FedML
33
7
0
08 Nov 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
17
22
0
06 Oct 2022
Federated Boosted Decision Trees with Differential Privacy
Federated Boosted Decision Trees with Differential Privacy
Samuel Maddock
Graham Cormode
Tianhao Wang
Carsten Maple
S. Jha
FedML
26
29
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
54
102
0
30 Jun 2022
Differentially Private Fine-tuning of Language Models
Differentially Private Fine-tuning of Language Models
Da Yu
Saurabh Naik
A. Backurs
Sivakanth Gopi
Huseyin A. Inan
...
Y. Lee
Andre Manoel
Lukas Wutschitz
Sergey Yekhanin
Huishuai Zhang
134
347
0
13 Oct 2021
Opacus: User-Friendly Differential Privacy Library in PyTorch
Opacus: User-Friendly Differential Privacy Library in PyTorch
Ashkan Yousefpour
I. Shilov
Alexandre Sablayrolles
Davide Testuggine
Karthik Prasad
...
Sayan Gosh
Akash Bharadwaj
Jessica Zhao
Graham Cormode
Ilya Mironov
VLM
159
350
0
25 Sep 2021
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
1,815
0
14 Dec 2020
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