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
Unleashing the Power of Randomization in Auditing Differentially Private ML Krishna Pillutla Galen Andrew Peter Kairouz H. B. McMahan Alina Oprea Sewoong Oh 43 20 0 29 May 2023
Alteration-free and Model-agnostic Origin Attribution of Generated Images Zhenting Wang Chen Chen Yi Zeng Lingjuan Lyu Shiqing Ma 30 5 0 29 May 2023
NOTABLE: Transferable Backdoor Attacks Against Prompt-based NLP Models Kai Mei Zheng Li Zhenting Wang Yang Zhang Shiqing Ma AAML SILM 39 48 0 28 May 2023
An Efficient Membership Inference Attack for the Diffusion Model by Proximal Initialization Fei Kong Jinhao Duan Ruipeng Ma Hengtao Shen Xiao-lan Zhu Xiaoshuang Shi Kaidi Xu DiffM 31 30 0 26 May 2023
Rethinking Certification for Trustworthy Machine Learning-Based Applications M. Anisetti C. Ardagna Nicola Bena Ernesto Damiani 17 9 0 26 May 2023
DP-SGD Without Clipping: The Lipschitz Neural Network Way Louis Bethune Thomas Massena Thibaut Boissin Yannick Prudent Corentin Friedrich Franck Mamalet A. Bellet M. Serrurier David Vigouroux 39 9 0 25 May 2023
Training Data Extraction From Pre-trained Language Models: A Survey Shotaro Ishihara 41 46 0 25 May 2023
A Survey on ChatGPT: AI-Generated Contents, Challenges, and Solutions Yuntao Wang Yanghe Pan Miao Yan Zhou Su Tom H. Luan 37 148 0 25 May 2023
Flocks of Stochastic Parrots: Differentially Private Prompt Learning for Large Language Models Haonan Duan Adam Dziedzic Nicolas Papernot Franziska Boenisch AAML 24 62 0 24 May 2023
Trade-Offs Between Fairness and Privacy in Language Modeling Cleo Matzken Steffen Eger Ivan Habernal SILM 46 6 0 24 May 2023
Domain Private Transformers for Multi-Domain Dialog Systems Anmol Kabra Ethan R. Elenberg 24 0 0 23 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
Watermarking Text Data on Large Language Models for Dataset Copyright Yixin Liu Hongsheng Hu Xun Chen Xuyun Zhang Lichao Sun WaLM 26 22 0 22 May 2023
Causality-Aided Trade-off Analysis for Machine Learning Fairness Zhenlan Ji Pingchuan Ma Shuai Wang Yanhui Li FaML 39 7 0 22 May 2023
Evaluating Privacy Leakage in Split Learning Xinchi Qiu Ilias Leontiadis Luca Melis Alex Sablayrolles Pierre Stock 38 5 0 22 May 2023
FSSA: Efficient 3-Round Secure Aggregation for Privacy-Preserving Federated Learning Fucai Luo Saif M. Al-Kuwari Haiyan Wang Xingfu Yan 19 1 0 22 May 2023
The "code'' of Ethics:A Holistic Audit of AI Code Generators Wanlun Ma Yiliao Song Minhui Xue Sheng Wen Yang Xiang 27 4 0 22 May 2023
Has It All Been Solved? Open NLP Research Questions Not Solved by Large Language Models Oana Ignat Zhijing Jin Artem Abzaliev Laura Biester Santiago Castro ... Verónica Pérez-Rosas Siqi Shen Zekun Wang Winston Wu Rada Mihalcea LRM 46 6 0 21 May 2023
SneakyPrompt: Jailbreaking Text-to-image Generative Models Yuchen Yang Bo Hui Haolin Yuan Neil Zhenqiang Gong Yinzhi Cao EGVM 46 74 0 20 May 2023
TSGM: A Flexible Framework for Generative Modeling of Synthetic Time Series Alexander Nikitin Letizia Iannucci Samuel Kaski TTA SyDa AI4TS 41 11 0 19 May 2023
PS-FedGAN: An Efficient Federated Learning Framework Based on Partially Shared Generative Adversarial Networks For Data Privacy Achintha Wijesinghe Songyang Zhang Zhi Ding FedML 37 7 0 19 May 2023
Rapid Adaptation in Online Continual Learning: Are We Evaluating It Right? Hasan Hammoud Ameya Prabhu Ser-Nam Lim Philip Torr Adel Bibi Guohao Li CLL 116 16 0 16 May 2023
Privacy-Preserving Ensemble Infused Enhanced Deep Neural Network Framework for Edge Cloud Convergence Veronika Stephanie I. Khalil Mohammad Saidur Rahman Mohammed Atiquzzaman FedML 13 10 0 16 May 2023
Trustworthy Privacy-preserving Hierarchical Ensemble and Federated Learning in Healthcare 4.0 with Blockchain Veronika Stephanie Ibrahim Khalil Mohammed Atiquzzaman X. Yi 30 24 0 16 May 2023
Private Training Set Inspection in MLaaS Mingxue Xu Tongtong Xu Po-Yu Chen 19 0 0 15 May 2023
Privacy Auditing with One (1) Training Run Thomas Steinke Milad Nasr Matthew Jagielski 58 77 0 15 May 2023
Automating privacy decisions -- where to draw the line? Victor Morel S. Fischer-Hübner 21 1 0 15 May 2023
Learn to Unlearn: A Survey on Machine Unlearning Youyang Qu Xinnan Yuan Ming Ding W. Ni Thierry Rakotoarivelo David Smith MU 9 0 0 12 May 2023
Securing Distributed SGD against Gradient Leakage Threats Wenqi Wei Ling Liu Jingya Zhou Ka-Ho Chow Yanzhao Wu FedML 39 18 0 10 May 2023
DPMLBench: Holistic Evaluation of Differentially Private Machine Learning Chengkun Wei Ming-Hui Zhao Zhikun Zhang Min Chen Wenlong Meng Bodong Liu Yuan-shuo Fan Wenzhi Chen 45 11 0 10 May 2023
Finding Meaningful Distributions of ML Black-boxes under Forensic Investigation Jiyi Zhang Hansheng Fang Hwee Kuan Lee E. Chang 35 1 0 10 May 2023
Energy-Latency Attacks to On-Device Neural Networks via Sponge Poisoning Zijian Wang Shuo Huang Yu-Jen Huang Helei Cui SILM 27 10 0 06 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 Comprehensive Study on Dataset Distillation: Performance, Privacy, Robustness and Fairness Zongxiong Chen Jiahui Geng Derui Zhu Herbert Woisetschlaeger Qing Li Sonja Schimmler Ruben Mayer Chunming Rong DD 31 9 0 05 May 2023
A Survey on Dataset Distillation: Approaches, Applications and Future Directions Jiahui Geng Zongxiong Chen Yuandou Wang Herbert Woisetschlaeger Sonja Schimmler Ruben Mayer Zhiming Zhao Chunming Rong DD 67 26 0 03 May 2023
Efficient Federated Learning with Enhanced Privacy via Lottery Ticket Pruning in Edge Computing Yi Shi Kang Wei Li Shen Jun Li Xueqian Wang Bo Yuan Song Guo 46 5 0 02 May 2023
Exactly Optimal and Communication-Efficient Private Estimation via Block Designs Hyun-Young Park Seungsoo Nam Si-Hyeon Lee 39 3 0 02 May 2023
Towards the Flatter Landscape and Better Generalization in Federated Learning under Client-level Differential Privacy Yi Shi Kang Wei Li Shen Yingqi Liu Xueqian Wang Bo Yuan Dacheng Tao FedML 46 2 0 01 May 2023
GTree: GPU-Friendly Privacy-preserving Decision Tree Training and Inference Qifan Wang Shujie Cui Lei Zhou Ye Dong Jianli Bai Yun Sing Koh Giovanni Russello 33 0 0 01 May 2023
Speak, Memory: An Archaeology of Books Known to ChatGPT/GPT-4 Kent K. Chang Mackenzie Cramer Sandeep Soni David Bamman RALM 152 114 0 28 Apr 2023
Private Information Retrieval and Its Applications: An Introduction, Open Problems, Future Directions Sajani Vithana Zhusheng Wang S. Ulukus 40 5 0 27 Apr 2023
Do SSL Models Have Déjà Vu? A Case of Unintended Memorization in Self-supervised Learning Casey Meehan Florian Bordes Pascal Vincent Kamalika Chaudhuri Chuan Guo 41 18 0 26 Apr 2023
Model Extraction Attacks Against Reinforcement Learning Based Controllers Momina Sajid Yanning Shen Yasser Shoukry OffRL MIACV AAML 17 0 0 25 Apr 2023
Sparse Private LASSO Logistic Regression Amol Khanna Fred Lu Edward Raff Brian Testa 21 3 0 24 Apr 2023
LaMP: When Large Language Models Meet Personalization Alireza Salemi Sheshera Mysore Michael Bendersky Hamed Zamani RALM 24 211 0 22 Apr 2023
Differentially Private Synthetic Data Generation via Lipschitz-Regularised Variational Autoencoders Benedikt Groß Gerhard Wunder SyDa 32 2 0 22 Apr 2023
DPAF: Image Synthesis via Differentially Private Aggregation in Forward Phase Chih-Hsun Lin Chia-Yi Hsu Chia-Mu Yu Yang Cao Chun-ying Huang 41 1 0 20 Apr 2023
Sparsity in neural networks can improve their privacy Antoine Gonon Léon Zheng Clément Lalanne Quoc-Tung Le Guillaume Lauga Can Pouliquen 50 2 0 20 Apr 2023
GrOVe: Ownership Verification of Graph Neural Networks using Embeddings Asim Waheed Vasisht Duddu Nadarajah Asokan 40 9 0 17 Apr 2023
Practical Differentially Private and Byzantine-resilient Federated Learning Zihang Xiang Tianhao Wang Wanyu Lin Di Wang FedML 41 22 0 15 Apr 2023