Membership Inference Attacks against Machine Learning Models

18 October 2016

Papers citing "Membership Inference Attacks against Machine Learning Models"

50 / 2,058 papers shown

Title
SoK: Privacy-Preserving Data Synthesis Yuzheng Hu Fan Wu Yue Liu Yunhui Long Gonzalo Munilla Garrido Chang Ge Bolin Ding David A. Forsyth Bo Li D. Song 60 26 0 05 Jul 2023
ProPILE: Probing Privacy Leakage in Large Language Models Siwon Kim Sangdoo Yun Hwaran Lee Martin Gubri Sungroh Yoon Seong Joon Oh PILM 390 97 3 04 Jul 2023
Synthetic is all you need: removing the auxiliary data assumption for membership inference attacks against synthetic data Florent Guépin Matthieu Meeus Ana-Maria Cretu Yves-Alexandre de Montjoye 34 10 0 04 Jul 2023
Overconfidence is a Dangerous Thing: Mitigating Membership Inference Attacks by Enforcing Less Confident Prediction Zitao Chen Karthik Pattabiraman 18 20 0 04 Jul 2023
Pareto-Secure Machine Learning (PSML): Fingerprinting and Securing Inference Serving Systems Debopam Sanyal Jui-Tse Hung Manavi Agrawal Prahlad Jasti Shahab Nikkhoo S. Jha Tianhao Wang Sibin Mohan Alexey Tumanov 51 0 0 03 Jul 2023
Over-The-Air Federated Learning: Status Quo, Open Challenges, and Future Directions Bingnan Xiao Xichen Yu Wei Ni Xin Wang H. Vincent Poor 43 20 0 03 Jul 2023
CasTGAN: Cascaded Generative Adversarial Network for Realistic Tabular Data Synthesis Abdallah Alshantti Damiano Varagnolo Adil Rasheed Aria Rahmati Frank Westad 29 6 0 01 Jul 2023
FFPDG: Fast, Fair and Private Data Generation Weijie Xu Jinjin Zhao Francis Iannacci Bo Wang 38 11 0 30 Jun 2023
Federated Generative Learning with Foundation Models Jie Zhang Xiaohua Qi Bo Zhao FedML 44 21 0 28 Jun 2023
Incremental Learning on Food Instance Segmentation Huu-Thanh Nguyen Yu Cao Chong-Wah Ngo W. Chan CLL 18 2 0 28 Jun 2023
Ticketed Learning-Unlearning Schemes Badih Ghazi Pritish Kamath Ravi Kumar Pasin Manurangsi Ayush Sekhari Chiyuan Zhang MU 48 7 0 27 Jun 2023
Differentially Private Video Activity Recognition Zelun Luo Yuliang Zou Yijin Yang Zane Durante De-An Huang Zhiding Yu Chaowei Xiao L. Fei-Fei Anima Anandkumar PICV 40 4 0 27 Jun 2023
Privacy and Fairness in Federated Learning: on the Perspective of Trade-off Huiqiang Chen Tianqing Zhu Tao Zhang Wanlei Zhou Philip S. Yu FedML 34 43 0 25 Jun 2023
Locally Differentially Private Distributed Online Learning with Guaranteed Optimality Ziqin Chen Yongqiang Wang 39 4 0 25 Jun 2023
Deconstructing Classifiers: Towards A Data Reconstruction Attack Against Text Classification Models Adel M. Elmahdy A. Salem SILM 25 6 0 23 Jun 2023
Towards More Realistic Membership Inference Attacks on Large Diffusion Models Jan Dubiñski Antoni Kowalczuk Stanislaw Pawlak Przemyslaw Rokita Tomasz Trzciñski P. Morawiecki 39 28 0 22 Jun 2023
FDINet: Protecting against DNN Model Extraction via Feature Distortion Index Hongwei Yao Zheng Li Haiqin Weng Feng Xue Kui Ren Zhan Qin 46 4 0 20 Jun 2023
Edge Learning for 6G-enabled Internet of Things: A Comprehensive Survey of Vulnerabilities, Datasets, and Defenses M. Ferrag Othmane Friha B. Kantarci Norbert Tihanyi Lucas C. Cordeiro Merouane Debbah Djallel Hamouda Muna Al-Hawawreh K. Choo 40 44 0 17 Jun 2023
Achilles' Heels: Vulnerable Record Identification in Synthetic Data Publishing Matthieu Meeus Florent Guépin Ana-Maria Cretu Yves-Alexandre de Montjoye 67 23 0 17 Jun 2023
Evaluating Data Attribution for Text-to-Image Models Sheng-Yu Wang Alexei A. Efros Jun-Yan Zhu Richard Y. Zhang TDI 43 30 0 15 Jun 2023
Matching Pairs: Attributing Fine-Tuned Models to their Pre-Trained Large Language Models Myles Foley Ambrish Rawat Taesung Lee Yufang Hou Gabriele Picco Giulio Zizzo DeLMO 43 5 0 15 Jun 2023
Your Room is not Private: Gradient Inversion Attack on Reinforcement Learning Miao Li Wenhao Ding Ding Zhao AAML 35 0 0 15 Jun 2023
An Efficient and Multi-private Key Secure Aggregation for Federated Learning Xue Yang Zifeng Liu Xiaohu Tang Rongxing Lu Bo Liu FedML 19 5 0 15 Jun 2023
Augment then Smooth: Reconciling Differential Privacy with Certified Robustness Jiapeng Wu Atiyeh Ashari Ghomi David Glukhov Jesse C. Cresswell Franziska Boenisch Nicolas Papernot AAML 52 1 0 14 Jun 2023
A Unified Framework of Graph Information Bottleneck for Robustness and Membership Privacy Enyan Dai Limeng Cui Zhengyang Wang Xianfeng Tang Yinghan Wang Mo Cheng Bin Yin Suhang Wang AAML 30 14 0 14 Jun 2023
Fairness and Privacy-Preserving in Federated Learning: A Survey Taki Hasan Rafi Faiza Anan Noor Tahmid Hussain Dong-Kyu Chae FedML 45 39 0 14 Jun 2023
SRATTA : Sample Re-ATTribution Attack of Secure Aggregation in Federated Learning Tanguy Marchand Regis Loeb Ulysse Marteau-Ferey Jean Ogier du Terrail Arthur Pignet FedML 44 4 0 13 Jun 2023
Gaussian Membership Inference Privacy Tobias Leemann Martin Pawelczyk Gjergji Kasneci 33 15 0 12 Jun 2023
AnoFel: Supporting Anonymity for Privacy-Preserving Federated Learning Ghada Almashaqbeh Zahra Ghodsi FedML 39 1 0 12 Jun 2023
One-Shot Machine Unlearning with Mnemonic Code Tomoya Yamashita Masanori Yamada Takashi Shibata MU 21 1 0 09 Jun 2023
PriSampler: Mitigating Property Inference of Diffusion Models Hailong Hu Jun Pang DiffM 20 3 0 08 Jun 2023
Investigating the Effect of Misalignment on Membership Privacy in the White-box Setting Ana-Maria Cretu Daniel Jones Yves-Alexandre de Montjoye Shruti Tople AAML 26 4 0 08 Jun 2023
Differentially Private Image Classification by Learning Priors from Random Processes Xinyu Tang Ashwinee Panda Vikash Sehwag Prateek Mittal 36 20 0 08 Jun 2023
Extracting Cloud-based Model with Prior Knowledge Songtao Zhao Kangjie Chen Meng Hao Jian Zhang Guowen Xu Hongwei Li Tianwei Zhang AAML MIACV SILM MLAU SLR 41 5 0 07 Jun 2023
Membership inference attack with relative decision boundary distance Jiacheng Xu Chengxiang Tan 41 1 0 07 Jun 2023
PILLAR: How to make semi-private learning more effective Francesco Pinto Yaxian Hu Fanny Yang Amartya Sanyal 57 11 0 06 Jun 2023
Avoid Adversarial Adaption in Federated Learning by Multi-Metric Investigations T. Krauß Alexandra Dmitrienko AAML 29 4 0 06 Jun 2023
Machine Unlearning: A Survey Heng Xu Tianqing Zhu Lefeng Zhang Wanlei Zhou Philip S. Yu MU 46 19 0 06 Jun 2023
Discriminative Adversarial Privacy: Balancing Accuracy and Membership Privacy in Neural Networks Eugenio Lomurno Alberto Archetti Francesca Ausonio Matteo Matteucci AAML 30 4 0 05 Jun 2023
Forgettable Federated Linear Learning with Certified Data Removal Rui Jin Minghui Chen Qiong Zhang Xiaoxiao Li MU 18 11 0 03 Jun 2023
Training Data Attribution for Diffusion Models Zheng Dai David K Gifford TDI 25 17 0 03 Jun 2023
Guiding Text-to-Text Privatization by Syntax Stefan Arnold Dilara Yesilbas Sven Weinzierl 30 8 0 02 Jun 2023
On Knowledge Editing in Federated Learning: Perspectives, Challenges, and Future Directions Leijie Wu Song Guo Junxiao Wang Zicong Hong Jie Zhang Jingren Zhou KELM 57 4 0 02 Jun 2023
TMI! Finetuned Models Leak Private Information from their Pretraining Data John Abascal Stanley Wu Alina Oprea Jonathan R. Ullman 44 16 0 01 Jun 2023
Challenges and Remedies to Privacy and Security in AIGC: Exploring the Potential of Privacy Computing, Blockchain, and Beyond Chuan Chen Zhenpeng Wu Yan-Hao Lai Wen-chao Ou Tianchi Liao Zibin Zheng 40 33 0 01 Jun 2023
ModelObfuscator: Obfuscating Model Information to Protect Deployed ML-based Systems Mingyi Zhou Xiang Gao Jing Wu John C. Grundy Xiao Chen Chunyang Chen Li Li AAML 44 12 0 01 Jun 2023
A Note On Interpreting Canary Exposure Matthew Jagielski 25 4 0 31 May 2023
Surrogate Model Extension (SME): A Fast and Accurate Weight Update Attack on Federated Learning Junyi Zhu Ruicong Yao Matthew B. Blaschko FedML 8 9 0 31 May 2023
Quantifying Overfitting: Evaluating Neural Network Performance through Analysis of Null Space Hossein Rezaei Mohammad Sabokrou 29 3 0 30 May 2023
Membership Inference Attacks against Language Models via Neighbourhood Comparison Justus Mattern Fatemehsadat Mireshghallah Zhijing Jin Bernhard Schölkopf Mrinmaya Sachan Taylor Berg-Kirkpatrick MIALM 28 169 0 29 May 2023