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1806.01246
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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
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Papers citing
"ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models"
50 / 519 papers shown
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139
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Binghui Zhang
Yuan Hong
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302
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0
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Exploring Privacy and Fairness Risks in Sharing Diffusion Models: An Adversarial Perspective
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Yangfan Jiang
Fei Wei
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181
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Is My Data in Your AI? Membership Inference Test (MINT) applied to Face Biometrics
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Julian Fierrez
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Ruben Tolosana
J. Ortega-Garcia
CVBM
400
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Discriminative Adversarial Unlearning
Rohan Sharma
Shijie Zhou
Kaiyi Ji
Changyou Chen
MU
168
1
0
10 Feb 2024
FedMIA: An Effective Membership Inference Attack Exploiting "All for One" Principle in Federated Learning
Gongxi Zhu
Donghao Li
Hanlin Gu
Yuxing Han
Yuan Yao
Lixin Fan
234
1
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09 Feb 2024
Mitigating Privacy Risk in Membership Inference by Convex-Concave Loss
Zhenlong Liu
Lei Feng
Huiping Zhuang
Xiaofeng Cao
Jianguo Huang
310
3
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08 Feb 2024
Security and Privacy Challenges of Large Language Models: A Survey
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M. H. Amini
Yanzhao Wu
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383
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30 Jan 2024
Decentralized Federated Learning: A Survey on Security and Privacy
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R. Razavi-Far
R. Razavi-Far
Boyu Wang
Qiang Yang
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269
89
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Inference Attacks Against Face Recognition Model without Classification Layers
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Huilong Chen
Yinggui Wang
Lei Wang
181
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Unraveling Attacks in Machine Learning-based IoT Ecosystems: A Survey and the Open Libraries Behind Them
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Boxi Chen
Wei Shao
Chris Zhang
Kelvin Wong
Yi Zhang
317
7
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22 Jan 2024
Federated Unlearning for Human Activity Recognition
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Dongping Zhang
Yaping Chai
Weibin Zhang
Shaowei Wang
Jiaxing Shen
MU
134
36
0
17 Jan 2024
FedTabDiff: Federated Learning of Diffusion Probabilistic Models for Synthetic Mixed-Type Tabular Data Generation
Timur Sattarov
Marco Schreyer
Damian Borth
FedML
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143
11
0
11 Jan 2024
Learning-Based Difficulty Calibration for Enhanced Membership Inference Attacks
European Symposium on Security and Privacy (EuroS&P), 2024
Haonan Shi
Ouyang Tu
An Wang
296
4
0
10 Jan 2024
Safety and Performance, Why Not Both? Bi-Objective Optimized Model Compression against Heterogeneous Attacks Toward AI Software Deployment
IEEE Transactions on Software Engineering (TSE), 2024
Jie Zhu
Leye Wang
Xiao Han
Anmin Liu
Tao Xie
AAML
203
6
0
02 Jan 2024
Privacy-Preserved Neural Graph Databases
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Haoran Li
Jiaxin Bai
Zihao Wang
Yangqiu Song
329
3
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PPIDSG: A Privacy-Preserving Image Distribution Sharing Scheme with GAN in Federated Learning
AAAI Conference on Artificial Intelligence (AAAI), 2023
Yuting Ma
Yuanzhi Yao
Xiaohua Xu
FedML
151
7
0
16 Dec 2023
Black-box Membership Inference Attacks against Fine-tuned Diffusion Models
Network and Distributed System Security Symposium (NDSS), 2023
Yan Pang
Tianhao Wang
361
34
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13 Dec 2023
Diffence: Fencing Membership Privacy With Diffusion Models
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Ali Naseh
Amir Houmansadr
AAML
327
4
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07 Dec 2023
Low-Cost High-Power Membership Inference Attacks
International Conference on Machine Learning (ICML), 2023
Sajjad Zarifzadeh
Philippe Liu
Reza Shokri
333
74
0
06 Dec 2023
All Rivers Run to the Sea: Private Learning with Asymmetric Flows
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Yue Niu
Ramy E. Ali
Saurav Prakash
Salman Avestimehr
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351
2
0
05 Dec 2023
DUCK: Distance-based Unlearning via Centroid Kinematics
Marco Cotogni
Jacopo Bonato
Luigi Sabetta
Francesco Pelosin
Alessandro Nicolosi
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420
16
0
04 Dec 2023
Refine, Discriminate and Align: Stealing Encoders via Sample-Wise Prototypes and Multi-Relational Extraction
European Conference on Computer Vision (ECCV), 2023
Shuchi Wu
Chuan Ma
Kang Wei
Xiaogang Xu
Ming Ding
Yuwen Qian
Tao Xiang
216
1
0
01 Dec 2023
MIA-BAD: An Approach for Enhancing Membership Inference Attack and its Mitigation with Federated Learning
International Conference on Computing, Networking and Communications (ICNC), 2023
Soumya Banerjee
Sandip Roy
Sayyed Farid Ahamed
Devin Quinn
Marc Vucovich
Dhruv Nandakumar
K. Choi
Abdul Rahman
Edward Bowen
Sachin Shetty
246
9
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DPSUR: Accelerating Differentially Private Stochastic Gradient Descent Using Selective Update and Release
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Jie Fu
Qingqing Ye
Haibo Hu
Zhili Chen
Lulu Wang
Kuncan Wang
Xun Ran
280
25
0
23 Nov 2023
Practical Membership Inference Attacks against Fine-tuned Large Language Models via Self-prompt Calibration
Neural Information Processing Systems (NeurIPS), 2023
Wenjie Fu
Huandong Wang
Chen Gao
Guanghua Liu
Yong Li
Tao Jiang
MIALM
488
30
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Moritz Knolle
Georgios Kaissis
317
1
0
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ERASER: Machine Unlearning in MLaaS via an Inference Serving-Aware Approach
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Yuke Hu
Jian Lou
Jiaqi Liu
Wangze Ni
Feng Lin
Zhan Qin
Kui Ren
MU
311
25
0
03 Nov 2023
MIST: Defending Against Membership Inference Attacks Through Membership-Invariant Subspace Training
USENIX Security Symposium (USENIX Security), 2023
Jiacheng Li
Ninghui Li
Bruno Ribeiro
334
6
0
02 Nov 2023
Generated Distributions Are All You Need for Membership Inference Attacks Against Generative Models
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Minxing Zhang
Ning Yu
Rui Wen
Michael Backes
Yang Zhang
DiffM
185
30
0
30 Oct 2023
Where have you been? A Study of Privacy Risk for Point-of-Interest Recommendation
Knowledge Discovery and Data Mining (KDD), 2023
Kunlin Cai
Jinghuai Zhang
Zhiqing Hong
Will Shand
Guang Wang
Desheng Zhang
Jianfeng Chi
Yuan Tian
326
6
0
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Fundamental Limits of Membership Inference Attacks on Machine Learning Models
Eric Aubinais
Elisabeth Gassiat
Pablo Piantanida
MIACV
493
4
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20 Oct 2023
SecurityNet: Assessing Machine Learning Vulnerabilities on Public Models
Boyang Zhang
Zheng Li
Ziqing Yang
Xinlei He
Michael Backes
Mario Fritz
Yang Zhang
337
8
0
19 Oct 2023
Quantifying Privacy Risks of Prompts in Visual Prompt Learning
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Yixin Wu
Rui Wen
Michael Backes
Pascal Berrang
Mathias Humbert
Yun Shen
Yang Zhang
AAML
VPVLM
256
11
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18 Oct 2023
Last One Standing: A Comparative Analysis of Security and Privacy of Soft Prompt Tuning, LoRA, and In-Context Learning
Rui Wen
Tianhao Wang
Michael Backes
Yang Zhang
Ahmed Salem
AAML
185
18
0
17 Oct 2023
Passive Inference Attacks on Split Learning via Adversarial Regularization
Network and Distributed System Security Symposium (NDSS), 2023
Xiaochen Zhu
Xinjian Luo
Yuncheng Wu
Yangfan Jiang
Xiaokui Xiao
Beng Chin Ooi
FedML
335
11
0
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A Comprehensive Study of Privacy Risks in Curriculum Learning
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Joann Qiongna Chen
Xinlei He
Zheng Li
Yang Zhang
Zhou Li
263
2
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Improved Membership Inference Attacks Against Language Classification Models
Shlomit Shachor
N. Razinkov
Abigail Goldsteen
319
7
0
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No Privacy Left Outside: On the (In-)Security of TEE-Shielded DNN Partition for On-Device ML
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Yifeng Cai
Yuanyuan Yuan
Bingyan Liu
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Yao Guo
Xiangqun Chen
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185
41
0
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Secure Decentralized Learning with Blockchain
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Yifan Hua
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177
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Making Users Indistinguishable: Attribute-wise Unlearning in Recommender Systems
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Chaochao Chen
Xiaolin Zheng
Yizhao Zhang
Zhongxuan Han
Dan Meng
Jun Wang
MU
154
33
0
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StegGuard: Fingerprinting Self-supervised Pre-trained Encoders via Secrets Embeder and Extractor
Xingdong Ren
Tianxing Zhang
Hanzhou Wu
Xinpeng Zhang
Yinggui Wang
Guangling Sun
LLMSV
258
0
0
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Source Inference Attacks: Beyond Membership Inference Attacks in Federated Learning
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Hongsheng Hu
Xuyun Zhang
Z. Salcic
Lichao Sun
K. Choo
Gillian Dobbie
178
27
0
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Pratiksha Agrawal
Pratiksha Agrawal
Johannes O. Royset
Rajiv Khanna
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379
3
0
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A Duty to Forget, a Right to be Assured? Exposing Vulnerabilities in Machine Unlearning Services
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Hongsheng Hu
Shuo Wang
Jiamin Chang
Haonan Zhong
Ruoxi Sun
Shuang Hao
Haojin Zhu
Minhui Xue
MU
232
42
0
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SLMIA-SR: Speaker-Level Membership Inference Attacks against Speaker Recognition Systems
Network and Distributed System Security Symposium (NDSS), 2023
Guangke Chen
Yedi Zhang
Fu Song
235
13
0
14 Sep 2023
A Survey on Privacy in Graph Neural Networks: Attacks, Preservation, and Applications
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Yuying Zhao
Zhaoqing Li
Xueqi Cheng
Yu Wang
Olivera Kotevska
Philip S. Yu
Hanyu Wang
349
29
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Lu Cheng
182
3
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Balancing Transparency and Risk: The Security and Privacy Risks of Open-Source Machine Learning Models
Dominik Hintersdorf
Lukas Struppek
Kristian Kersting
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153
6
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