Label-Only Membership Inference Attacks

28 July 2020

Christopher A. Choquette-Choo

Papers citing "Label-Only Membership Inference Attacks"

50 / 115 papers shown

Title
Nosy Layers, Noisy Fixes: Tackling DRAs in Federated Learning Systems using Explainable AI Meghali Nandi Arash Shaghaghi Nazatul Haque Sultan Gustavo Batista Raymond K. Zhao Sanjay Jha AAML 12 0 0 16 May 2025
Cutting Through Privacy: A Hyperplane-Based Data Reconstruction Attack in Federated Learning Francesco Diana André Nusser Chuan Xu Giovanni Neglia 27 0 0 15 May 2025
On the Account Security Risks Posed by Password Strength Meters Ming Xu Weili Han Jitao Yu Jing Liu Xinsong Zhang Yun Lin Jin Song Dong 34 0 0 13 May 2025
Threat Modeling for AI: The Case for an Asset-Centric Approach Jose Sanchez Vicarte Marcin Spoczynski Mostafa Elsaid 34 0 0 08 May 2025
Privacy Risks and Preservation Methods in Explainable Artificial Intelligence: A Scoping Review Sonal Allana Mohan Kankanhalli Rozita Dara 35 0 0 05 May 2025
DeSIA: Attribute Inference Attacks Against Limited Fixed Aggregate Statistics Yifeng Mao Bozhidar Stevanoski Yves-Alexandre de Montjoye 52 0 0 25 Apr 2025
DC-SGD: Differentially Private SGD with Dynamic Clipping through Gradient Norm Distribution Estimation Chengkun Wei Weixian Li Chen Gong Wenzhi Chen 60 0 0 29 Mar 2025
Do Fairness Interventions Come at the Cost of Privacy: Evaluations for Binary Classifiers Huan Tian Guangsheng Zhang Bo Liu Tianqing Zhu Ming Ding Wanlei Zhou 58 0 0 08 Mar 2025
Towards Label-Only Membership Inference Attack against Pre-trained Large Language Models Yu He Boheng Li L. Liu Zhongjie Ba Wei Dong Yiming Li Zhanyue Qin Kui Ren Chong Chen MIALM 74 0 0 26 Feb 2025
Privacy Ripple Effects from Adding or Removing Personal Information in Language Model Training Jaydeep Borkar Matthew Jagielski Katherine Lee Niloofar Mireshghallah David A. Smith Christopher A. Choquette-Choo PILM 85 1 0 24 Feb 2025
The Canary's Echo: Auditing Privacy Risks of LLM-Generated Synthetic Text Matthieu Meeus Lukas Wutschitz Santiago Zanella Béguelin Shruti Tople Reza Shokri 85 0 0 24 Feb 2025
Guarding the Privacy of Label-Only Access to Neural Network Classifiers via iDP Verification Anan Kabaha Dana Drachsler-Cohen AAML 50 0 0 23 Feb 2025
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 66 34 0 20 Jan 2025
GRID: Protecting Training Graph from Link Stealing Attacks on GNN Models Jiadong Lou Xu Yuan Rui Zhang Xingliang Yuan Neil Gong N. Tzeng AAML 45 1 0 19 Jan 2025
Understanding and Mitigating Membership Inference Risks of Neural Ordinary Differential Equations Sanghyun Hong Fan Wu A. Gruber Kookjin Lee 47 0 0 12 Jan 2025
Synthetic Data Privacy Metrics Amy Steier Lipika Ramaswamy Andre Manoel Alexa Haushalter 53 0 0 08 Jan 2025
Gradients Stand-in for Defending Deep Leakage in Federated Learning H. Yi H. Ren C. Hu Y. Li J. Deng Xin Xie FedML 35 0 0 11 Oct 2024
Ward: Provable RAG Dataset Inference via LLM Watermarks Nikola Jovanović Robin Staab Maximilian Baader Martin Vechev 199 1 0 04 Oct 2024
A Cost-Aware Approach to Adversarial Robustness in Neural Networks Charles Meyers Mohammad Reza Saleh Sedghpour Tommy Löfstedt Erik Elmroth OOD AAML 33 0 0 11 Sep 2024
Membership Inference Attack Against Masked Image Modeling Zehan Li Xinlei He Ning Yu Yang Zhang 44 1 0 13 Aug 2024
Range Membership Inference Attacks Jiashu Tao Reza Shokri 48 1 0 09 Aug 2024
Differentially Private Block-wise Gradient Shuffle for Deep Learning Zilong Zhang FedML 45 0 0 31 Jul 2024
Fingerprint Membership and Identity Inference Against Generative Adversarial Networks Saverio Cavasin Daniele Mari Simone Milani Mauro Conti AAML 34 3 0 21 Jun 2024
Label Smoothing Improves Machine Unlearning Zonglin Di Zhaowei Zhu Jinghan Jia Jiancheng Liu Zafar Takhirov Bo Jiang Yuanshun Yao Sijia Liu Yang Liu 42 2 0 11 Jun 2024
OSLO: One-Shot Label-Only Membership Inference Attacks Yuefeng Peng Jaechul Roh Subhransu Maji Amir Houmansadr 44 0 0 27 May 2024
Efficient Knowledge Deletion from Trained Models through Layer-wise Partial Machine Unlearning Vinay Chakravarthi Gogineni E. Nadimi MU 31 1 0 12 Mar 2024
SoK: Unintended Interactions among Machine Learning Defenses and Risks Vasisht Duddu S. Szyller Nadarajah Asokan AAML 49 2 0 07 Dec 2023
All Rivers Run to the Sea: Private Learning with Asymmetric Flows Yue Niu Ramy E. Ali Saurav Prakash Salman Avestimehr FedML 38 2 0 05 Dec 2023
Beyond Boundaries: A Comprehensive Survey of Transferable Attacks on AI Systems Guangjing Wang Ce Zhou Yuanda Wang Bocheng Chen Hanqing Guo Qiben Yan AAML SILM 68 3 0 20 Nov 2023
Assessing Privacy Risks in Language Models: A Case Study on Summarization Tasks Ruixiang Tang Gord Lueck Rodolfo Quispe Huseyin A. Inan Janardhan Kulkarni Xia Hu 31 6 0 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 42 4 0 19 Oct 2023
Defending Our Privacy With Backdoors Dominik Hintersdorf Lukas Struppek Daniel Neider Kristian Kersting SILM AAML 26 2 0 12 Oct 2023
White-box Membership Inference Attacks against Diffusion Models Yan Pang Tianhao Wang Xu Kang Mengdi Huai Yang Zhang AAML DiffM 48 22 0 11 Aug 2023
Latent Code Augmentation Based on Stable Diffusion for Data-free Substitute Attacks Mingwen Shao Lingzhuang Meng Yuanjian Qiao Lixu Zhang W. Zuo DiffM 29 0 0 24 Jul 2023
FFPDG: Fast, Fair and Private Data Generation Weijie Xu Jinjin Zhao Francis Iannacci Bo Wang 36 11 0 30 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
Membership inference attack with relative decision boundary distance Jiacheng Xu Chengxiang Tan 26 1 0 07 Jun 2023
Training Data Extraction From Pre-trained Language Models: A Survey Shotaro Ishihara 37 46 0 25 May 2023
Differentially Private Synthetic Data via Foundation Model APIs 1: Images Zinan Lin Sivakanth Gopi Janardhan Kulkarni Harsha Nori Sergey Yekhanin 43 37 0 24 May 2023
Selective Pre-training for Private Fine-tuning Da Yu Sivakanth Gopi Janardhan Kulkarni Zinan Lin Saurabh Naik Tomasz Religa Jian Yin Huishuai Zhang 43 19 0 23 May 2023
Gradient Leakage Defense with Key-Lock Module for Federated Learning Hanchi Ren Jingjing Deng Xianghua Xie Xiaoke Ma Jianfeng Ma FedML 37 2 0 06 May 2023
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
Students Parrot Their Teachers: Membership Inference on Model Distillation Matthew Jagielski Milad Nasr Christopher A. Choquette-Choo Katherine Lee Nicholas Carlini FedML 43 21 0 06 Mar 2023
Membership Inference Attack for Beluga Whales Discrimination Voncarlos Marcelo Araújo Sébastien Gambs Clément Chion Robert Michaud L. Schneider H. Lautraite 33 2 0 28 Feb 2023
Prompt Stealing Attacks Against Text-to-Image Generation Models Xinyue Shen Y. Qu Michael Backes Yang Zhang 30 32 0 20 Feb 2023
AUTOLYCUS: Exploiting Explainable AI (XAI) for Model Extraction Attacks against Interpretable Models Abdullah Çaglar Öksüz Anisa Halimi Erman Ayday ELM AAML 23 2 0 04 Feb 2023
Are Diffusion Models Vulnerable to Membership Inference Attacks? Jinhao Duan Fei Kong Shiqi Wang Xiaoshuang Shi Kaidi Xu 35 109 0 02 Feb 2023
Learning to Unlearn: Instance-wise Unlearning for Pre-trained Classifiers Sungmin Cha Sungjun Cho Dasol Hwang Honglak Lee Taesup Moon Moontae Lee MU 49 36 0 27 Jan 2023
Threats, Vulnerabilities, and Controls of Machine Learning Based Systems: A Survey and Taxonomy Yusuke Kawamoto Kazumasa Miyake K. Konishi Y. Oiwa 29 4 0 18 Jan 2023
GAN-based Domain Inference Attack Yuechun Gu Keke Chen 15 11 0 22 Dec 2022