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MemGuard: Defending against Black-Box Membership Inference Attacks via
  Adversarial Examples

MemGuard: Defending against Black-Box Membership Inference Attacks via Adversarial Examples

23 September 2019
Jinyuan Jia
Ahmed Salem
Michael Backes
Yang Zhang
Neil Zhenqiang Gong
ArXivPDFHTML

Papers citing "MemGuard: Defending against Black-Box Membership Inference Attacks via Adversarial Examples"

50 / 65 papers shown
Title
AugMixCloak: A Defense against Membership Inference Attacks via Image Transformation
AugMixCloak: A Defense against Membership Inference Attacks via Image Transformation
Heqing Ren
Chao Feng
Alberto Huertas
Burkhard Stiller
21
0
0
11 May 2025
Privacy Risks and Preservation Methods in Explainable Artificial Intelligence: A Scoping Review
Privacy Risks and Preservation Methods in Explainable Artificial Intelligence: A Scoping Review
Sonal Allana
Mohan Kankanhalli
Rozita Dara
32
0
0
05 May 2025
What's Pulling the Strings? Evaluating Integrity and Attribution in AI Training and Inference through Concept Shift
What's Pulling the Strings? Evaluating Integrity and Attribution in AI Training and Inference through Concept Shift
Jiamin Chang
Hao Li
Hammond Pearce
Ruoxi Sun
Bo-wen Li
Minhui Xue
38
0
0
28 Apr 2025
CENSOR: Defense Against Gradient Inversion via Orthogonal Subspace Bayesian Sampling
Kaiyuan Zhang
Siyuan Cheng
Guangyu Shen
Bruno Ribeiro
Shengwei An
Pin-Yu Chen
Xinming Zhang
Ninghui Li
102
1
0
28 Jan 2025
Rethinking Membership Inference Attacks Against Transfer Learning
Rethinking Membership Inference Attacks Against Transfer Learning
Yanwei Yue
Jing Chen
Qianru Fang
Kun He
Ziming Zhao
Hao Ren
Guowen Xu
Yang Liu
Yang Xiang
64
34
0
20 Jan 2025
GRID: Protecting Training Graph from Link Stealing Attacks on GNN Models
GRID: Protecting Training Graph from Link Stealing Attacks on GNN Models
Jiadong Lou
Xu Yuan
Rui Zhang
Xingliang Yuan
Neil Gong
N. Tzeng
AAML
42
1
0
19 Jan 2025
Understanding and Mitigating Membership Inference Risks of Neural Ordinary Differential Equations
Understanding and Mitigating Membership Inference Risks of Neural Ordinary Differential Equations
Sanghyun Hong
Fan Wu
A. Gruber
Kookjin Lee
42
0
0
12 Jan 2025
Membership Inference Attack Against Masked Image Modeling
Membership Inference Attack Against Masked Image Modeling
Zehan Li
Xinlei He
Ning Yu
Yang Zhang
42
1
0
13 Aug 2024
A Survey on Machine Unlearning: Techniques and New Emerged Privacy Risks
A Survey on Machine Unlearning: Techniques and New Emerged Privacy Risks
Hengzhu Liu
Ping Xiong
Tianqing Zhu
Philip S. Yu
32
6
0
10 Jun 2024
Trustworthy Distributed AI Systems: Robustness, Privacy, and Governance
Trustworthy Distributed AI Systems: Robustness, Privacy, and Governance
Wenqi Wei
Ling Liu
31
16
0
02 Feb 2024
SecurityNet: Assessing Machine Learning Vulnerabilities on Public Models
SecurityNet: Assessing Machine Learning Vulnerabilities on Public Models
Boyang Zhang
Zheng Li
Ziqing Yang
Xinlei He
Michael Backes
Mario Fritz
Yang Zhang
30
4
0
19 Oct 2023
A Survey on Privacy in Graph Neural Networks: Attacks, Preservation, and
  Applications
A Survey on Privacy in Graph Neural Networks: Attacks, Preservation, and Applications
Yi Zhang
Yuying Zhao
Zhaoqing Li
Xueqi Cheng
Yu-Chiang Frank Wang
Olivera Kotevska
Philip S. Yu
Tyler Derr
26
10
0
31 Aug 2023
Membership inference attack with relative decision boundary distance
Membership inference attack with relative decision boundary distance
Jiacheng Xu
Chengxiang Tan
26
1
0
07 Jun 2023
Privacy Protectability: An Information-theoretical Approach
Privacy Protectability: An Information-theoretical Approach
Siping Shi
Bihai Zhang
Dan Wang
23
1
0
25 May 2023
Finding Meaningful Distributions of ML Black-boxes under Forensic
  Investigation
Finding Meaningful Distributions of ML Black-boxes under Forensic Investigation
Jiyi Zhang
Hansheng Fang
Hwee Kuan Lee
E. Chang
16
1
0
10 May 2023
FACE-AUDITOR: Data Auditing in Facial Recognition Systems
FACE-AUDITOR: Data Auditing in Facial Recognition Systems
Min Chen
Zhikun Zhang
Tianhao Wang
Michael Backes
Yang Zhang
CVBM
30
14
0
05 Apr 2023
A Survey on Secure and Private Federated Learning Using Blockchain:
  Theory and Application in Resource-constrained Computing
A Survey on Secure and Private Federated Learning Using Blockchain: Theory and Application in Resource-constrained Computing
Ervin Moore
Ahmed Imteaj
S. Rezapour
M. Amini
33
18
0
24 Mar 2023
"Real Attackers Don't Compute Gradients": Bridging the Gap Between
  Adversarial ML Research and Practice
"Real Attackers Don't Compute Gradients": Bridging the Gap Between Adversarial ML Research and Practice
Giovanni Apruzzese
Hyrum S. Anderson
Savino Dambra
D. Freeman
Fabio Pierazzi
Kevin A. Roundy
AAML
31
75
0
29 Dec 2022
Purifier: Defending Data Inference Attacks via Transforming Confidence
  Scores
Purifier: Defending Data Inference Attacks via Transforming Confidence Scores
Ziqi Yang
Li-Juan Wang
D. Yang
Jie Wan
Ziming Zhao
E. Chang
Fan Zhang
Kui Ren
AAML
24
15
0
01 Dec 2022
SoK: Secure Human-centered Wireless Sensing
SoK: Secure Human-centered Wireless Sensing
Wei Sun
Tingjun Chen
Neil Zhenqiang Gong
24
5
0
22 Nov 2022
On the Vulnerability of Data Points under Multiple Membership Inference
  Attacks and Target Models
On the Vulnerability of Data Points under Multiple Membership Inference Attacks and Target Models
Mauro Conti
Jiaxin Li
S. Picek
MIALM
32
2
0
28 Oct 2022
Membership Inference Attacks and Generalization: A Causal Perspective
Membership Inference Attacks and Generalization: A Causal Perspective
Teodora Baluta
Shiqi Shen
S. Hitarth
Shruti Tople
Prateek Saxena
OOD
MIACV
40
18
0
18 Sep 2022
On the Privacy Risks of Cell-Based NAS Architectures
On the Privacy Risks of Cell-Based NAS Architectures
Haiping Huang
Zhikun Zhang
Yun Shen
Michael Backes
Qi Li
Yang Zhang
27
7
0
04 Sep 2022
Membership Inference Attacks by Exploiting Loss Trajectory
Membership Inference Attacks by Exploiting Loss Trajectory
Yiyong Liu
Zhengyu Zhao
Michael Backes
Yang Zhang
21
98
0
31 Aug 2022
Data Isotopes for Data Provenance in DNNs
Data Isotopes for Data Provenance in DNNs
Emily Wenger
Xiuyu Li
Ben Y. Zhao
Vitaly Shmatikov
20
12
0
29 Aug 2022
Membership-Doctor: Comprehensive Assessment of Membership Inference
  Against Machine Learning Models
Membership-Doctor: Comprehensive Assessment of Membership Inference Against Machine Learning Models
Xinlei He
Zheng Li
Weilin Xu
Cory Cornelius
Yang Zhang
MIACV
30
24
0
22 Aug 2022
Private, Efficient, and Accurate: Protecting Models Trained by
  Multi-party Learning with Differential Privacy
Private, Efficient, and Accurate: Protecting Models Trained by Multi-party Learning with Differential Privacy
Wenqiang Ruan
Ming Xu
Wenjing Fang
Li Wang
Lei Wang
Wei Han
32
12
0
18 Aug 2022
Federated and Transfer Learning: A Survey on Adversaries and Defense
  Mechanisms
Federated and Transfer Learning: A Survey on Adversaries and Defense Mechanisms
Ehsan Hallaji
R. Razavi-Far
M. Saif
AAML
FedML
21
13
0
05 Jul 2022
NeuGuard: Lightweight Neuron-Guided Defense against Membership Inference
  Attacks
NeuGuard: Lightweight Neuron-Guided Defense against Membership Inference Attacks
Nuo Xu
Binghui Wang
Ran Ran
Wujie Wen
Parv Venkitasubramaniam
AAML
18
5
0
11 Jun 2022
Dataset Distillation using Neural Feature Regression
Dataset Distillation using Neural Feature Regression
Yongchao Zhou
E. Nezhadarya
Jimmy Ba
DD
FedML
39
149
0
01 Jun 2022
Membership Inference Attack Using Self Influence Functions
Membership Inference Attack Using Self Influence Functions
Gilad Cohen
Raja Giryes
TDI
30
12
0
26 May 2022
How to Combine Membership-Inference Attacks on Multiple Updated Models
How to Combine Membership-Inference Attacks on Multiple Updated Models
Matthew Jagielski
Stanley Wu
Alina Oprea
Jonathan R. Ullman
Roxana Geambasu
26
10
0
12 May 2022
Truth Serum: Poisoning Machine Learning Models to Reveal Their Secrets
Truth Serum: Poisoning Machine Learning Models to Reveal Their Secrets
Florian Tramèr
Reza Shokri
Ayrton San Joaquin
Hoang Minh Le
Matthew Jagielski
Sanghyun Hong
Nicholas Carlini
MIACV
36
107
0
31 Mar 2022
One Parameter Defense -- Defending against Data Inference Attacks via
  Differential Privacy
One Parameter Defense -- Defending against Data Inference Attacks via Differential Privacy
Dayong Ye
Sheng Shen
Tianqing Zhu
B. Liu
Wanlei Zhou
MIACV
16
61
0
13 Mar 2022
MIAShield: Defending Membership Inference Attacks via Preemptive
  Exclusion of Members
MIAShield: Defending Membership Inference Attacks via Preemptive Exclusion of Members
Ismat Jarin
Birhanu Eshete
29
9
0
02 Mar 2022
Membership Inference Attacks and Defenses in Neural Network Pruning
Membership Inference Attacks and Defenses in Neural Network Pruning
Xiaoyong Yuan
Lan Zhang
AAML
16
44
0
07 Feb 2022
Redactor: A Data-centric and Individualized Defense Against Inference
  Attacks
Redactor: A Data-centric and Individualized Defense Against Inference Attacks
Geon Heo
Steven Euijong Whang
AAML
20
2
0
07 Feb 2022
LTU Attacker for Membership Inference
LTU Attacker for Membership Inference
Joseph Pedersen
Rafael Munoz-Gómez
Jiangnan Huang
Haozhe Sun
Wei-Wei Tu
Isabelle M Guyon
29
1
0
04 Feb 2022
StolenEncoder: Stealing Pre-trained Encoders in Self-supervised Learning
StolenEncoder: Stealing Pre-trained Encoders in Self-supervised Learning
Yupei Liu
Jinyuan Jia
Hongbin Liu
Neil Zhenqiang Gong
MIACV
8
25
0
15 Jan 2022
Model Stealing Attacks Against Inductive Graph Neural Networks
Model Stealing Attacks Against Inductive Graph Neural Networks
Yun Shen
Xinlei He
Yufei Han
Yang Zhang
19
60
0
15 Dec 2021
Membership Inference Attacks From First Principles
Membership Inference Attacks From First Principles
Nicholas Carlini
Steve Chien
Milad Nasr
Shuang Song
Andreas Terzis
Florian Tramèr
MIACV
MIALM
29
639
0
07 Dec 2021
SHAPr: An Efficient and Versatile Membership Privacy Risk Metric for
  Machine Learning
SHAPr: An Efficient and Versatile Membership Privacy Risk Metric for Machine Learning
Vasisht Duddu
S. Szyller
Nadarajah Asokan
24
12
0
04 Dec 2021
Lightweight machine unlearning in neural network
Lightweight machine unlearning in neural network
Kongyang Chen
Yiwen Wang
Yao Huang
MU
20
7
0
10 Nov 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
14
9
0
11 Oct 2021
The Connection between Out-of-Distribution Generalization and Privacy of
  ML Models
The Connection between Out-of-Distribution Generalization and Privacy of ML Models
Divyat Mahajan
Shruti Tople
Amit Sharma
OOD
21
7
0
07 Oct 2021
Membership Inference Attacks Against Recommender Systems
Membership Inference Attacks Against Recommender Systems
Minxing Zhang
Z. Ren
Zihan Wang
Pengjie Ren
Zhumin Chen
Pengfei Hu
Yang Zhang
MIACV
AAML
26
83
0
16 Sep 2021
EncoderMI: Membership Inference against Pre-trained Encoders in
  Contrastive Learning
EncoderMI: Membership Inference against Pre-trained Encoders in Contrastive Learning
Hongbin Liu
Jinyuan Jia
Wenjie Qu
Neil Zhenqiang Gong
4
94
0
25 Aug 2021
Privacy-Preserving Machine Learning: Methods, Challenges and Directions
Privacy-Preserving Machine Learning: Methods, Challenges and Directions
Runhua Xu
Nathalie Baracaldo
J. Joshi
29
100
0
10 Aug 2021
Membership Inference Attack and Defense for Wireless Signal Classifiers
  with Deep Learning
Membership Inference Attack and Defense for Wireless Signal Classifiers with Deep Learning
Yi Shi
Y. Sagduyu
13
16
0
22 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
PILM
MIACV
19
71
0
04 Jul 2021
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