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  4. Cited By
ML-Leaks: Model and Data Independent Membership Inference Attacks and
  Defenses on Machine Learning Models

ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models

4 June 2018
A. Salem
Yang Zhang
Mathias Humbert
Pascal Berrang
Mario Fritz
Michael Backes
    MIACV
    MIALM
ArXivPDFHTML

Papers citing "ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models"

50 / 465 papers shown
Title
DP$^2$-FedSAM: Enhancing Differentially Private Federated Learning
  Through Personalized Sharpness-Aware Minimization
DP2^22-FedSAM: Enhancing Differentially Private Federated Learning Through Personalized Sharpness-Aware Minimization
Zhenxiao Zhang
Yuanxiong Guo
Yanmin Gong
FedML
38
0
0
20 Sep 2024
Data Poisoning and Leakage Analysis in Federated Learning
Data Poisoning and Leakage Analysis in Federated Learning
Wenqi Wei
Tiansheng Huang
Zachary Yahn
Anoop Singhal
Margaret Loper
Ling Liu
FedML
SILM
28
0
0
19 Sep 2024
Understanding Data Importance in Machine Learning Attacks: Does Valuable
  Data Pose Greater Harm?
Understanding Data Importance in Machine Learning Attacks: Does Valuable Data Pose Greater Harm?
Rui Wen
Michael Backes
Yang Zhang
TDI
AAML
41
0
0
05 Sep 2024
Membership Inference Attacks Against In-Context Learning
Membership Inference Attacks Against In-Context Learning
Rui Wen
Z. Li
Michael Backes
Yang Zhang
37
6
0
02 Sep 2024
Unveiling the Vulnerability of Private Fine-Tuning in Split-Based
  Frameworks for Large Language Models: A Bidirectionally Enhanced Attack
Unveiling the Vulnerability of Private Fine-Tuning in Split-Based Frameworks for Large Language Models: A Bidirectionally Enhanced Attack
Guanzhong Chen
Zhenghan Qin
Mingxin Yang
Yajie Zhou
Tao Fan
Tianyu Du
Zenglin Xu
AAML
53
4
0
02 Sep 2024
Is Difficulty Calibration All We Need? Towards More Practical Membership
  Inference Attacks
Is Difficulty Calibration All We Need? Towards More Practical Membership Inference Attacks
Yu He
Boheng Li
Yao Wang
Mengda Yang
Juan Wang
Hongxin Hu
Xingyu Zhao
27
4
0
31 Aug 2024
Analyzing Inference Privacy Risks Through Gradients in Machine Learning
Analyzing Inference Privacy Risks Through Gradients in Machine Learning
Zhuohang Li
Andrew Lowy
Jing Liu
T. Koike-Akino
K. Parsons
Bradley Malin
Ye Wang
FedML
32
1
0
29 Aug 2024
Inside the Black Box: Detecting Data Leakage in Pre-trained Language
  Encoders
Inside the Black Box: Detecting Data Leakage in Pre-trained Language Encoders
Yuan Xin
Z. Li
Ning Yu
Dingfan Chen
Mario Fritz
Michael Backes
Yang Zhang
PILM
MIACV
34
2
0
20 Aug 2024
Membership Inference Attack Against Masked Image Modeling
Membership Inference Attack Against Masked Image Modeling
Z. Li
Xinlei He
Ning Yu
Yang Zhang
42
1
0
13 Aug 2024
Deep Learning with Data Privacy via Residual Perturbation
Deep Learning with Data Privacy via Residual Perturbation
Wenqi Tao
Huaming Ling
Zuoqiang Shi
Bao Wang
21
2
0
11 Aug 2024
Attacks and Defenses for Generative Diffusion Models: A Comprehensive
  Survey
Attacks and Defenses for Generative Diffusion Models: A Comprehensive Survey
V. T. Truong
Luan Ba Dang
Long Bao Le
DiffM
MedIm
50
16
0
06 Aug 2024
Adaptive Differentially Private Structural Entropy Minimization for
  Unsupervised Social Event Detection
Adaptive Differentially Private Structural Entropy Minimization for Unsupervised Social Event Detection
Zhiwei Yang
Yuecen Wei
Haoran Li
Qian Li
Lei Jiang
Li Sun
Xiaoyan Yu
Chunming Hu
Hao Peng
46
2
0
23 Jul 2024
Representation Magnitude has a Liability to Privacy Vulnerability
Representation Magnitude has a Liability to Privacy Vulnerability
Xingli Fang
Jung-Eun Kim
21
1
0
23 Jul 2024
SeqMIA: Sequential-Metric Based Membership Inference Attack
SeqMIA: Sequential-Metric Based Membership Inference Attack
Hao Li
Zheng Li
Siyuan Wu
Chengrui Hu
Yutong Ye
Min Zhang
Dengguo Feng
Yang Zhang
32
3
0
21 Jul 2024
Unveiling Structural Memorization: Structural Membership Inference
  Attack for Text-to-Image Diffusion Models
Unveiling Structural Memorization: Structural Membership Inference Attack for Text-to-Image Diffusion Models
Qiao Li
Xiaomeng Fu
Xi Wang
Jin Liu
Xingyu Gao
Jiao Dai
Jizhong Han
28
3
0
18 Jul 2024
Feature Inference Attack on Shapley Values
Feature Inference Attack on Shapley Values
Xinjian Luo
Yangfan Jiang
X. Xiao
AAML
FAtt
38
19
0
16 Jul 2024
Learning to Unlearn for Robust Machine Unlearning
Learning to Unlearn for Robust Machine Unlearning
Mark He Huang
Lin Geng Foo
Jun Liu
MU
37
8
0
15 Jul 2024
Threats and Defenses in Federated Learning Life Cycle: A Comprehensive
  Survey and Challenges
Threats and Defenses in Federated Learning Life Cycle: A Comprehensive Survey and Challenges
Yanli Li
Zhongliang Guo
Nan Yang
Huaming Chen
Dong Yuan
Weiping Ding
FedML
37
2
0
09 Jul 2024
Synthetic Data: Revisiting the Privacy-Utility Trade-off
Synthetic Data: Revisiting the Privacy-Utility Trade-off
Fatima Jahan Sarmin
Atiquer Rahman Sarkar
Yang Wang
Noman Mohammed
32
3
0
09 Jul 2024
A Method to Facilitate Membership Inference Attacks in Deep Learning
  Models
A Method to Facilitate Membership Inference Attacks in Deep Learning Models
Zitao Chen
Karthik Pattabiraman
MIACV
MLAU
AAML
MIALM
67
1
0
02 Jul 2024
Silver Linings in the Shadows: Harnessing Membership Inference for
  Machine Unlearning
Silver Linings in the Shadows: Harnessing Membership Inference for Machine Unlearning
Nexhi Sula
Abhinav Kumar
Jie Hou
Han Wang
R. Tourani
MU
25
0
0
01 Jul 2024
Dataset Size Recovery from LoRA Weights
Dataset Size Recovery from LoRA Weights
Mohammad Salama
Jonathan Kahana
Eliahu Horwitz
Yedid Hoshen
39
5
0
27 Jun 2024
A Zero Auxiliary Knowledge Membership Inference Attack on Aggregate
  Location Data
A Zero Auxiliary Knowledge Membership Inference Attack on Aggregate Location Data
Vincent Guan
Florent Guépin
Ana-Maria Cretu
Yves-Alexandre de Montjoye
26
3
0
26 Jun 2024
Fingerprint Membership and Identity Inference Against Generative
  Adversarial Networks
Fingerprint Membership and Identity Inference Against Generative Adversarial Networks
Saverio Cavasin
Daniele Mari
Simone Milani
Mauro Conti
AAML
26
3
0
21 Jun 2024
Graph Transductive Defense: a Two-Stage Defense for Graph Membership
  Inference Attacks
Graph Transductive Defense: a Two-Stage Defense for Graph Membership Inference Attacks
Peizhi Niu
Chao Pan
Siheng Chen
Olgica Milenkovic
AAML
35
0
0
12 Jun 2024
Rethinking the impact of noisy labels in graph classification: A utility
  and privacy perspective
Rethinking the impact of noisy labels in graph classification: A utility and privacy perspective
De Li
Xianxian Li
Zeming Gan
Qiyu Li
Bin Qu
Jinyan Wang
NoLa
40
1
0
11 Jun 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
Inference Attacks: A Taxonomy, Survey, and Promising Directions
Inference Attacks: A Taxonomy, Survey, and Promising Directions
Feng Wu
Lei Cui
Shaowen Yao
Shui Yu
41
2
0
04 Jun 2024
OSLO: One-Shot Label-Only Membership Inference Attacks
OSLO: One-Shot Label-Only Membership Inference Attacks
Yuefeng Peng
Jaechul Roh
Subhransu Maji
Amir Houmansadr
44
0
0
27 May 2024
Towards Black-Box Membership Inference Attack for Diffusion Models
Towards Black-Box Membership Inference Attack for Diffusion Models
Jingwei Li
Jingyi Dong
Tianxing He
Jingzhao Zhang
25
3
0
25 May 2024
Lost in the Averages: A New Specific Setup to Evaluate Membership
  Inference Attacks Against Machine Learning Models
Lost in the Averages: A New Specific Setup to Evaluate Membership Inference Attacks Against Machine Learning Models
Florent Guépin
Natasa Krco
Matthieu Meeus
Yves-Alexandre de Montjoye
31
1
0
24 May 2024
Decaf: Data Distribution Decompose Attack against Federated Learning
Decaf: Data Distribution Decompose Attack against Federated Learning
Zhiyang Dai
Chunyi Zhou
Anmin Fu
26
2
0
24 May 2024
Leakage-Resilient and Carbon-Neutral Aggregation Featuring the Federated
  AI-enabled Critical Infrastructure
Leakage-Resilient and Carbon-Neutral Aggregation Featuring the Federated AI-enabled Critical Infrastructure
Zehang Deng
Ruoxi Sun
Minhui Xue
Sheng Wen
S. Çamtepe
Surya Nepal
Yang Xiang
39
1
0
24 May 2024
Data Contamination Calibration for Black-box LLMs
Data Contamination Calibration for Black-box LLMs
Wen-song Ye
Jiaqi Hu
Liyao Li
Haobo Wang
Gang Chen
Junbo Zhao
40
6
0
20 May 2024
Private Data Leakage in Federated Human Activity Recognition for
  Wearable Healthcare Devices
Private Data Leakage in Federated Human Activity Recognition for Wearable Healthcare Devices
Kongyang Chen
Dongping Zhang
Sijia Guan
Bing Mi
Jiaxing Shen
Guoqing Wang
FedML
34
1
0
14 May 2024
Shadow-Free Membership Inference Attacks: Recommender Systems Are More
  Vulnerable Than You Thought
Shadow-Free Membership Inference Attacks: Recommender Systems Are More Vulnerable Than You Thought
Xiaoxiao Chi
Xuyun Zhang
Yan Wang
Lianyong Qi
Amin Beheshti
Xiaolong Xu
Kim-Kwang Raymond Choo
Shuo Wang
Hongsheng Hu
39
0
0
11 May 2024
Link Stealing Attacks Against Inductive Graph Neural Networks
Link Stealing Attacks Against Inductive Graph Neural Networks
Yixin Wu
Xinlei He
Pascal Berrang
Mathias Humbert
Michael Backes
Neil Zhenqiang Gong
Yang Zhang
34
2
0
09 May 2024
Federated Graph Condensation with Information Bottleneck Principles
Federated Graph Condensation with Information Bottleneck Principles
Bo Yan
DD
FedML
37
4
0
07 May 2024
Does Your Neural Code Completion Model Use My Code? A Membership
  Inference Approach
Does Your Neural Code Completion Model Use My Code? A Membership Inference Approach
Yao Wan
Guanghua Wan
Shijie Zhang
Hongyu Zhang
Yulei Sui
Pan Zhou
Hai Jin
Lichao Sun
27
2
0
22 Apr 2024
Is Retain Set All You Need in Machine Unlearning? Restoring Performance
  of Unlearned Models with Out-Of-Distribution Images
Is Retain Set All You Need in Machine Unlearning? Restoring Performance of Unlearned Models with Out-Of-Distribution Images
Jacopo Bonato
Marco Cotogni
Luigi Sabetta
MU
CLL
42
4
0
19 Apr 2024
Towards a Game-theoretic Understanding of Explanation-based Membership
  Inference Attacks
Towards a Game-theoretic Understanding of Explanation-based Membership Inference Attacks
Kavita Kumari
Murtuza Jadliwala
S. Jha
Anindya Maiti
42
2
0
10 Apr 2024
Goldfish: An Efficient Federated Unlearning Framework
Goldfish: An Efficient Federated Unlearning Framework
Houzhe Wang
Xiaojie Zhu
Chi Chen
Paulo Esteves-Verissimo
FedML
MU
31
3
0
04 Apr 2024
A Unified Membership Inference Method for Visual Self-supervised Encoder
  via Part-aware Capability
A Unified Membership Inference Method for Visual Self-supervised Encoder via Part-aware Capability
Jie Zhu
Jirong Zha
Ding Li
Leye Wang
37
6
0
03 Apr 2024
Digital Forgetting in Large Language Models: A Survey of Unlearning
  Methods
Digital Forgetting in Large Language Models: A Survey of Unlearning Methods
Alberto Blanco-Justicia
N. Jebreel
Benet Manzanares-Salor
David Sánchez
Josep Domingo-Ferrer
Guillem Collell
Kuan Eeik Tan
KELM
MU
39
17
0
02 Apr 2024
A Survey of Privacy-Preserving Model Explanations: Privacy Risks,
  Attacks, and Countermeasures
A Survey of Privacy-Preserving Model Explanations: Privacy Risks, Attacks, and Countermeasures
Thanh Tam Nguyen
T. T. Huynh
Zhao Ren
Thanh Toan Nguyen
Phi Le Nguyen
Hongzhi Yin
Quoc Viet Hung Nguyen
65
8
0
31 Mar 2024
MisGUIDE : Defense Against Data-Free Deep Learning Model Extraction
MisGUIDE : Defense Against Data-Free Deep Learning Model Extraction
Mahendra Gurve
S. Behera
Satyadev Ahlawat
Yamuna Prasad
MIACV
AAML
29
0
0
27 Mar 2024
Model Will Tell: Training Membership Inference for Diffusion Models
Model Will Tell: Training Membership Inference for Diffusion Models
Xiaomeng Fu
Xi Wang
Qiao Li
Jin Liu
Jiao Dai
Jizhong Han
47
5
0
13 Mar 2024
EdgeLeakage: Membership Information Leakage in Distributed Edge
  Intelligence Systems
EdgeLeakage: Membership Information Leakage in Distributed Edge Intelligence Systems
Kongyang Chen
Yi Lin
Hui Luo
Bing Mi
Yatie Xiao
Chao Ma
Jorge Sá Silva
19
3
0
08 Mar 2024
Inf2Guard: An Information-Theoretic Framework for Learning
  Privacy-Preserving Representations against Inference Attacks
Inf2Guard: An Information-Theoretic Framework for Learning Privacy-Preserving Representations against Inference Attacks
Sayedeh Leila Noorbakhsh
Binghui Zhang
Yuan Hong
Binghui Wang
AAML
25
8
0
04 Mar 2024
Exploring Privacy and Fairness Risks in Sharing Diffusion Models: An
  Adversarial Perspective
Exploring Privacy and Fairness Risks in Sharing Diffusion Models: An Adversarial Perspective
Xinjian Luo
Yangfan Jiang
Fei Wei
Yuncheng Wu
Xiaokui Xiao
Beng Chin Ooi
DiffM
38
4
0
28 Feb 2024
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