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  4. Cited By
The Secret Sharer: Evaluating and Testing Unintended Memorization in
  Neural Networks
v1v2v3 (latest)

The Secret Sharer: Evaluating and Testing Unintended Memorization in Neural Networks

22 February 2018
Nicholas Carlini
Chang-rui Liu
Ulfar Erlingsson
Jernej Kos
Basel Alomair
ArXiv (abs)PDFHTML

Papers citing "The Secret Sharer: Evaluating and Testing Unintended Memorization in Neural Networks"

50 / 441 papers shown
Title
Enhanced Membership Inference Attacks against Machine Learning Models
Enhanced Membership Inference Attacks against Machine Learning Models
Jiayuan Ye
Aadyaa Maddi
S. K. Murakonda
Vincent Bindschaedler
Reza Shokri
MIALMMIACV
116
257
0
18 Nov 2021
How much do language models copy from their training data? Evaluating
  linguistic novelty in text generation using RAVEN
How much do language models copy from their training data? Evaluating linguistic novelty in text generation using RAVEN
R. Thomas McCoy
P. Smolensky
Tal Linzen
Jianfeng Gao
Asli Celikyilmaz
SyDa
94
124
0
18 Nov 2021
On the Importance of Difficulty Calibration in Membership Inference
  Attacks
On the Importance of Difficulty Calibration in Membership Inference Attacks
Lauren Watson
Chuan Guo
Graham Cormode
Alex Sablayrolles
111
135
0
15 Nov 2021
Property Inference Attacks Against GANs
Property Inference Attacks Against GANs
Junhao Zhou
Yufei Chen
Chao Shen
Yang Zhang
AAMLMIACV
107
55
0
15 Nov 2021
The Role of Adaptive Optimizers for Honest Private Hyperparameter
  Selection
The Role of Adaptive Optimizers for Honest Private Hyperparameter Selection
Shubhankar Mohapatra
Sajin Sasy
Xi He
Gautam Kamath
Om Thakkar
164
33
0
09 Nov 2021
Get a Model! Model Hijacking Attack Against Machine Learning Models
Get a Model! Model Hijacking Attack Against Machine Learning Models
A. Salem
Michael Backes
Yang Zhang
AAML
101
28
0
08 Nov 2021
Privacy attacks for automatic speech recognition acoustic models in a
  federated learning framework
Privacy attacks for automatic speech recognition acoustic models in a federated learning framework
N. Tomashenko
Salima Mdhaffar
Marc Tommasi
Yannick Esteve
J. Bonastre
84
25
0
06 Nov 2021
Backdoor Pre-trained Models Can Transfer to All
Backdoor Pre-trained Models Can Transfer to All
Lujia Shen
S. Ji
Xuhong Zhang
Jinfeng Li
Jing Chen
Jie Shi
Chengfang Fang
Jianwei Yin
Ting Wang
AAMLSILM
102
131
0
30 Oct 2021
Mitigating Membership Inference Attacks by Self-Distillation Through a
  Novel Ensemble Architecture
Mitigating Membership Inference Attacks by Self-Distillation Through a Novel Ensemble Architecture
Xinyu Tang
Saeed Mahloujifar
Liwei Song
Virat Shejwalkar
Milad Nasr
Amir Houmansadr
Prateek Mittal
69
80
0
15 Oct 2021
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
262
373
0
13 Oct 2021
Generalization Techniques Empirically Outperform Differential Privacy
  against Membership Inference
Generalization Techniques Empirically Outperform Differential Privacy against Membership Inference
Jiaxiang Liu
Simon Oya
Florian Kerschbaum
MIACV
153
9
0
11 Oct 2021
Unrolling SGD: Understanding Factors Influencing Machine Unlearning
Unrolling SGD: Understanding Factors Influencing Machine Unlearning
Anvith Thudi
Gabriel Deza
Varun Chandrasekaran
Nicolas Papernot
MU
142
182
0
27 Sep 2021
Robin Hood and Matthew Effects: Differential Privacy Has Disparate
  Impact on Synthetic Data
Robin Hood and Matthew Effects: Differential Privacy Has Disparate Impact on Synthetic Data
Georgi Ganev
Bristena Oprisanu
Emiliano De Cristofaro
139
58
0
23 Sep 2021
SoK: Machine Learning Governance
SoK: Machine Learning Governance
Varun Chandrasekaran
Hengrui Jia
Anvith Thudi
Adelin Travers
Mohammad Yaghini
Nicolas Papernot
137
16
0
20 Sep 2021
Membership Inference Attacks Against Recommender Systems
Membership Inference Attacks Against Recommender Systems
Minxing Zhang
Zhaochun Ren
Zihan Wang
Pengjie Ren
Zhumin Chen
Pengfei Hu
Yang Zhang
MIACVAAML
83
90
0
16 Sep 2021
Source Inference Attacks in Federated Learning
Source Inference Attacks in Federated Learning
Hongsheng Hu
Z. Salcic
Lichao Sun
Gillian Dobbie
Xuyun Zhang
82
82
0
13 Sep 2021
EMA: Auditing Data Removal from Trained Models
EMA: Auditing Data Removal from Trained Models
Yangsibo Huang
Xiaoxiao Li
Kai Li
40
15
0
08 Sep 2021
Selective Differential Privacy for Language Modeling
Selective Differential Privacy for Language Modeling
Weiyan Shi
Aiqi Cui
Evan Li
R. Jia
Zhou Yu
89
73
0
30 Aug 2021
Differentially Private n-gram Extraction
Differentially Private n-gram Extraction
Kunho Kim
Sivakanth Gopi
Janardhan Kulkarni
Sergey Yekhanin
66
15
0
05 Aug 2021
Artificial Intelligence in Healthcare: Lost In Translation?
Artificial Intelligence in Healthcare: Lost In Translation?
V. Madai
David C. Higgins
18
4
0
28 Jul 2021
Private Alternating Least Squares: Practical Private Matrix Completion
  with Tighter Rates
Private Alternating Least Squares: Practical Private Matrix Completion with Tighter Rates
Steve Chien
Prateek Jain
Walid Krichene
Steffen Rendle
Shuang Song
Abhradeep Thakurta
Li Zhang
54
19
0
20 Jul 2021
This Person (Probably) Exists. Identity Membership Attacks Against GAN
  Generated Faces
This Person (Probably) Exists. Identity Membership Attacks Against GAN Generated Faces
Ryan Webster
Julien Rabin
Loïc Simon
F. Jurie
CVBMPICV
80
33
0
13 Jul 2021
Trustworthy AI: A Computational Perspective
Trustworthy AI: A Computational Perspective
Haochen Liu
Yiqi Wang
Wenqi Fan
Xiaorui Liu
Yaxin Li
Shaili Jain
Yunhao Liu
Anil K. Jain
Jiliang Tang
FaML
192
213
0
12 Jul 2021
Anticipating Safety Issues in E2E Conversational AI: Framework and
  Tooling
Anticipating Safety Issues in E2E Conversational AI: Framework and Tooling
Emily Dinan
Gavin Abercrombie
A. S. Bergman
Shannon L. Spruit
Dirk Hovy
Y-Lan Boureau
Verena Rieser
97
109
0
07 Jul 2021
RoFL: Robustness of Secure Federated Learning
RoFL: Robustness of Secure Federated Learning
Hidde Lycklama
Lukas Burkhalter
Alexander Viand
Nicolas Küchler
Anwar Hithnawi
FedML
88
63
0
07 Jul 2021
Optimizing the Numbers of Queries and Replies in Federated Learning with
  Differential Privacy
Optimizing the Numbers of Queries and Replies in Federated Learning with Differential Privacy
Yipeng Zhou
Xuezheng Liu
Yao Fu
Di Wu
Chao Li
Shui Yu
FedML
74
2
0
05 Jul 2021
Survey: Leakage and Privacy at Inference Time
Survey: Leakage and Privacy at Inference Time
Marija Jegorova
Chaitanya Kaul
Charlie Mayor
Alison Q. OÑeil
Alexander Weir
Roderick Murray-Smith
Sotirios A. Tsaftaris
PILMMIACV
113
75
0
04 Jul 2021
Privacy Budget Scheduling
Privacy Budget Scheduling
Tao Luo
Mingen Pan
Pierre Tholoniat
Asaf Cidon
Roxana Geambasu
Mathias Lécuyer
59
33
0
29 Jun 2021
Covariance-Aware Private Mean Estimation Without Private Covariance
  Estimation
Covariance-Aware Private Mean Estimation Without Private Covariance Estimation
Gavin Brown
Marco Gaboardi
Adam D. Smith
Jonathan R. Ullman
Lydia Zakynthinou
FedML
106
50
0
24 Jun 2021
Membership Inference on Word Embedding and Beyond
Membership Inference on Word Embedding and Beyond
Saeed Mahloujifar
Huseyin A. Inan
Melissa Chase
Esha Ghosh
Marcello Hasegawa
MIACVSILM
90
49
0
21 Jun 2021
Large Scale Private Learning via Low-rank Reparametrization
Large Scale Private Learning via Low-rank Reparametrization
Da Yu
Huishuai Zhang
Wei Chen
Jian Yin
Tie-Yan Liu
87
106
0
17 Jun 2021
Antipodes of Label Differential Privacy: PATE and ALIBI
Antipodes of Label Differential Privacy: PATE and ALIBI
Mani Malek
Ilya Mironov
Karthik Prasad
I. Shilov
Florian Tramèr
71
66
0
07 Jun 2021
On Memorization in Probabilistic Deep Generative Models
On Memorization in Probabilistic Deep Generative Models
G. V. D. Burg
Christopher K. I. Williams
TDI
95
63
0
06 Jun 2021
A unified PAC-Bayesian framework for machine unlearning via information
  risk minimization
A unified PAC-Bayesian framework for machine unlearning via information risk minimization
Sharu Theresa Jose
Osvaldo Simeone
MU
78
7
0
01 Jun 2021
Bounding Information Leakage in Machine Learning
Bounding Information Leakage in Machine Learning
Ganesh Del Grosso
Georg Pichler
C. Palamidessi
Pablo Piantanida
MIACVFedML
88
10
0
09 May 2021
Poisoning the Unlabeled Dataset of Semi-Supervised Learning
Poisoning the Unlabeled Dataset of Semi-Supervised Learning
Nicholas Carlini
AAML
220
68
0
04 May 2021
A Review of Confidentiality Threats Against Embedded Neural Network
  Models
A Review of Confidentiality Threats Against Embedded Neural Network Models
Raphael Joud
Pierre-Alain Moëllic
Rémi Bernhard
J. Rigaud
77
6
0
04 May 2021
Privacy-Preserving Portrait Matting
Privacy-Preserving Portrait Matting
Jizhizi Li
Sihan Ma
Jing Zhang
Dacheng Tao
PICV
81
63
0
29 Apr 2021
Memorisation versus Generalisation in Pre-trained Language Models
Memorisation versus Generalisation in Pre-trained Language Models
Michael Tänzer
Sebastian Ruder
Marek Rei
112
51
0
16 Apr 2021
Membership Inference Attacks on Knowledge Graphs
Membership Inference Attacks on Knowledge Graphs
Yu Wang
Lifu Huang
Philip S. Yu
Lichao Sun
MIACV
61
15
0
16 Apr 2021
A Method to Reveal Speaker Identity in Distributed ASR Training, and How
  to Counter It
A Method to Reveal Speaker Identity in Distributed ASR Training, and How to Counter It
Trung D. Q. Dang
Om Thakkar
Swaroop Indra Ramaswamy
Rajiv Mathews
Peter Chin
Franccoise Beaufays
FedML
53
10
0
15 Apr 2021
Nine Potential Pitfalls when Designing Human-AI Co-Creative Systems
Nine Potential Pitfalls when Designing Human-AI Co-Creative Systems
Daniel Buschek
Lukas Mecke
Florian Lehmann
Hai Dang
131
43
0
01 Apr 2021
DataLens: Scalable Privacy Preserving Training via Gradient Compression
  and Aggregation
DataLens: Scalable Privacy Preserving Training via Gradient Compression and Aggregation
Wei Ping
Fan Wu
Yunhui Long
Luka Rimanic
Ce Zhang
Yue Liu
FedML
133
66
0
20 Mar 2021
Membership Inference Attacks on Machine Learning: A Survey
Membership Inference Attacks on Machine Learning: A Survey
Hongsheng Hu
Z. Salcic
Lichao Sun
Gillian Dobbie
Philip S. Yu
Xuyun Zhang
MIACV
125
448
0
14 Mar 2021
Robust Model Compression Using Deep Hypotheses
Robust Model Compression Using Deep Hypotheses
Omri Armstrong
Ran Gilad-Bachrach
OOD
26
2
0
13 Mar 2021
Privacy Regularization: Joint Privacy-Utility Optimization in Language
  Models
Privacy Regularization: Joint Privacy-Utility Optimization in Language Models
Fatemehsadat Mireshghallah
Huseyin A. Inan
Marcello Hasegawa
Victor Rühle
Taylor Berg-Kirkpatrick
Robert Sim
47
43
0
12 Mar 2021
Private Cross-Silo Federated Learning for Extracting Vaccine Adverse
  Event Mentions
Private Cross-Silo Federated Learning for Extracting Vaccine Adverse Event Mentions
Pallika H. Kanani
Virendra J. Marathe
Daniel W. Peterson
R. Harpaz
Steve Bright
FedML
85
9
0
12 Mar 2021
Quantum machine learning with differential privacy
Quantum machine learning with differential privacy
William Watkins
Samuel Yen-Chi Chen
Shinjae Yoo
95
49
0
10 Mar 2021
A Study of Face Obfuscation in ImageNet
A Study of Face Obfuscation in ImageNet
Kaiyu Yang
Jacqueline Yau
Li Fei-Fei
Jia Deng
Olga Russakovsky
PICVCVBM
115
147
0
10 Mar 2021
Abstraction and Symbolic Execution of Deep Neural Networks with Bayesian
  Approximation of Hidden Features
Abstraction and Symbolic Execution of Deep Neural Networks with Bayesian Approximation of Hidden Features
Nicolas Berthier
Amany Alshareef
James Sharp
S. Schewe
Xiaowei Huang
74
10
0
05 Mar 2021
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