Canary in a Coalmine: Better Membership Inference with Ensembled Adversarial Queries

19 October 2022

Papers citing "Canary in a Coalmine: Better Membership Inference with Ensembled Adversarial Queries"

7 / 7 papers shown

Title
Has My System Prompt Been Used? Large Language Model Prompt Membership Inference Roman Levin Valeriia Cherepanova Abhimanyu Hans Avi Schwarzschild Tom Goldstein 111 1 0 14 Feb 2025
The Last Iterate Advantage: Empirical Auditing and Principled Heuristic Analysis of Differentially Private SGD Thomas Steinke Milad Nasr Arun Ganesh Borja Balle Christopher A. Choquette-Choo Matthew Jagielski Jamie Hayes Abhradeep Thakurta Adam Smith Andreas Terzis 23 7 0 08 Oct 2024
Universally Harmonizing Differential Privacy Mechanisms for Federated Learning: Boosting Accuracy and Convergence Shuya Feng Meisam Mohammady Hanbin Hong Shenao Yan Ashish Kundu Binghui Wang Yuan Hong FedML 34 3 0 20 Jul 2024
Parameters or Privacy: A Provable Tradeoff Between Overparameterization and Membership Inference Jasper Tan Blake Mason Hamid Javadi Richard G. Baraniuk FedML 29 19 0 02 Feb 2022
Patches Are All You Need? Asher Trockman J. Zico Kolter ViT 214 402 0 24 Jan 2022
Stochastic Training is Not Necessary for Generalization Jonas Geiping Micah Goldblum Phillip E. Pope Michael Moeller Tom Goldstein 81 72 0 29 Sep 2021
Systematic Evaluation of Privacy Risks of Machine Learning Models Liwei Song Prateek Mittal MIACV 185 358 0 24 Mar 2020