Low-Cost High-Power Membership Inference Attacks

6 December 2023

Papers citing "Low-Cost High-Power Membership Inference Attacks"

10 / 10 papers shown

Title
Privacy Risks and Preservation Methods in Explainable Artificial Intelligence: A Scoping Review Sonal Allana Mohan Kankanhalli Rozita Dara 27 0 0 05 May 2025
DeSIA: Attribute Inference Attacks Against Limited Fixed Aggregate Statistics Yifeng Mao Bozhidar Stevanoski Yves-Alexandre de Montjoye 45 0 0 25 Apr 2025
AMUN: Adversarial Machine UNlearning A. Boroojeny Hari Sundaram Varun Chandrasekaran MU AAML 43 0 0 02 Mar 2025
Are Neuromorphic Architectures Inherently Privacy-preserving? An Exploratory Study Ayana Moshruba Ihsen Alouani Maryam Parsa AAML 44 3 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 75 0 0 24 Feb 2025
On the Implicit Relation Between Low-Rank Adaptation and Differential Privacy Saber Malekmohammadi G. Farnadi 24 2 0 26 Sep 2024
Con-ReCall: Detecting Pre-training Data in LLMs via Contrastive Decoding Cheng Wang Yiwei Wang Bryan Hooi Yujun Cai Nanyun Peng Kai-Wei Chang 37 2 0 05 Sep 2024
Forget to Flourish: Leveraging Machine-Unlearning on Pretrained Language Models for Privacy Leakage Md. Rafi Ur Rashid Jing Liu T. Koike-Akino Shagufta Mehnaz Ye Wang MU SILM 31 3 0 30 Aug 2024
Extracting Training Data from Large Language Models Nicholas Carlini Florian Tramèr Eric Wallace Matthew Jagielski Ariel Herbert-Voss ... Tom B. Brown D. Song Ulfar Erlingsson Alina Oprea Colin Raffel MLAU SILM 267 1,808 0 14 Dec 2020
Systematic Evaluation of Privacy Risks of Machine Learning Models Liwei Song Prateek Mittal MIACV 185 358 0 24 Mar 2020