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Privacy Auditing with One (1) Training Run

Privacy Auditing with One (1) Training Run

15 May 2023
Thomas Steinke
Milad Nasr
Matthew Jagielski
ArXivPDFHTML

Papers citing "Privacy Auditing with One (1) Training Run"

13 / 13 papers shown
Title
DPImageBench: A Unified Benchmark for Differentially Private Image Synthesis
DPImageBench: A Unified Benchmark for Differentially Private Image Synthesis
Chen Gong
Kecen Li
Zinan Lin
Tianhao Wang
61
3
0
18 Mar 2025
Adversarial Sample-Based Approach for Tighter Privacy Auditing in Final Model-Only Scenarios
Adversarial Sample-Based Approach for Tighter Privacy Auditing in Final Model-Only Scenarios
Sangyeon Yoon
Wonje Jeung
Albert No
85
0
0
02 Dec 2024
The Last Iterate Advantage: Empirical Auditing and Principled Heuristic Analysis of Differentially Private SGD
The Last Iterate Advantage: Empirical Auditing and Principled Heuristic Analysis of Differentially Private SGD
Thomas Steinke
Milad Nasr
Arun Ganesh
Borja Balle
Christopher A. Choquette-Choo
Matthew Jagielski
Jamie Hayes
Abhradeep Thakurta
Adam Smith
Andreas Terzis
28
7
0
08 Oct 2024
Membership Inference Attacks Cannot Prove that a Model Was Trained On Your Data
Membership Inference Attacks Cannot Prove that a Model Was Trained On Your Data
Jie Zhang
Debeshee Das
Gautam Kamath
Florian Tramèr
MIALM
MIACV
228
16
1
29 Sep 2024
Laminator: Verifiable ML Property Cards using Hardware-assisted Attestations
Laminator: Verifiable ML Property Cards using Hardware-assisted Attestations
Vasisht Duddu
Oskari Jarvinen
Lachlan J. Gunn
Nirmal Asokan
67
1
0
25 Jun 2024
ATTAXONOMY: Unpacking Differential Privacy Guarantees Against Practical
  Adversaries
ATTAXONOMY: Unpacking Differential Privacy Guarantees Against Practical Adversaries
Rachel Cummings
Shlomi Hod
Jayshree Sarathy
Marika Swanberg
39
2
0
02 May 2024
Min-K%++: Improved Baseline for Detecting Pre-Training Data from Large Language Models
Min-K%++: Improved Baseline for Detecting Pre-Training Data from Large Language Models
Jingyang Zhang
Jingwei Sun
Eric C. Yeats
Ouyang Yang
Martin Kuo
Jianyi Zhang
Hao Frank Yang
Hai Li
43
41
0
03 Apr 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
TOFU: A Task of Fictitious Unlearning for LLMs
TOFU: A Task of Fictitious Unlearning for LLMs
Pratyush Maini
Zhili Feng
Avi Schwarzschild
Zachary Chase Lipton
J. Zico Kolter
MU
CLL
38
141
0
11 Jan 2024
Revealing the True Cost of Locally Differentially Private Protocols: An
  Auditing Perspective
Revealing the True Cost of Locally Differentially Private Protocols: An Auditing Perspective
Héber H. Arcolezi
Sébastien Gambs
30
1
0
04 Sep 2023
Epsilon*: Privacy Metric for Machine Learning Models
Epsilon*: Privacy Metric for Machine Learning Models
Diana M. Negoescu
H. González
Saad Eddin Al Orjany
Jilei Yang
Yuliia Lut
...
Xinyi Zheng
Zachariah Douglas
Vidita Nolkha
P. Ahammad
G. Samorodnitsky
28
2
0
21 Jul 2023
A Note On Interpreting Canary Exposure
A Note On Interpreting Canary Exposure
Matthew Jagielski
16
4
0
31 May 2023
Composition of Differential Privacy & Privacy Amplification by
  Subsampling
Composition of Differential Privacy & Privacy Amplification by Subsampling
Thomas Steinke
56
49
0
02 Oct 2022
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