Membership Inference Attacks are Easier on Difficult Problems

Membership Inference Attacks are Easier on Difficult Problems

15 February 2021

Papers citing "Membership Inference Attacks are Easier on Difficult Problems"

11 / 11 papers shown

Title
A Perplexity and Menger Curvature-Based Approach for Similarity Evaluation of Large Language Models Yuantao Zhang Zhankui Yang AAML 35 0 0 05 Apr 2025
Membership Inference Attacks and Defenses in Federated Learning: A Survey Li Bai Haibo Hu Qingqing Ye Haoyang Li Leixia Wang Jianliang Xu FedML 69 13 0 09 Dec 2024
Verification of Machine Unlearning is Fragile Binchi Zhang Zihan Chen Cong Shen Jundong Li AAML 71 5 0 01 Aug 2024
Dataset Size Recovery from LoRA Weights Mohammad Salama Jonathan Kahana Eliahu Horwitz Yedid Hoshen 39 5 0 27 Jun 2024
LLM Dataset Inference: Did you train on my dataset? Pratyush Maini Hengrui Jia Nicolas Papernot Adam Dziedzic MIALM 46 28 0 10 Jun 2024
Model Inversion Robustness: Can Transfer Learning Help? Sy-Tuyen Ho Koh Jun Hao Keshigeyan Chandrasegaran Ngoc-Bao Nguyen Ngai-man Cheung 42 8 0 09 May 2024
Recovering the Pre-Fine-Tuning Weights of Generative Models Eliahu Horwitz Jonathan Kahana Yedid Hoshen 50 9 0 15 Feb 2024
The Adversarial Implications of Variable-Time Inference Dudi Biton Aditi Misra Efrat Levy J. Kotak Ron Bitton R. Schuster Nicolas Papernot Yuval Elovici Ben Nassi AAML 20 0 0 05 Sep 2023
Leveraging Adversarial Examples to Quantify Membership Information Leakage Ganesh Del Grosso Hamid Jalalzai Georg Pichler C. Palamidessi Pablo Piantanida MIACV 29 21 0 17 Mar 2022
Membership Privacy Protection for Image Translation Models via Adversarial Knowledge Distillation Saeed Ranjbar Alvar Lanjun Wang Jiangbo Pei Yong Zhang VLM 12 2 0 10 Mar 2022
FedComm: Federated Learning as a Medium for Covert Communication Dorjan Hitaj Giulio Pagnotta B. Hitaj F. Pérez-Cruz L. Mancini FedML 25 10 0 21 Jan 2022