Pre-trained Encoder Inference: Revealing Upstream Encoders In Downstream Machine Learning Services
Authors: Shaopeng Fu, Xuexue Sun, Ke Qing, Tianhang Zheng, Di Wang | Published: 2024-08-05
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Pathway to Secure and Trustworthy ZSM for LLMs: Attacks, Defense, and Opportunities
Authors: Sunder Ali Khowaja, Parus Khuwaja, Kapal Dev, Hussam Al Hamadi, Engin Zeydan | Published: 2024-08-01 | Updated: 2025-01-06
Data Plagiarism Index: Characterizing the Privacy Risk of Data-Copying in Tabular Generative Models
Authors: Joshua Ward, Chi-Hua Wang, Guang Cheng | Published: 2024-06-18
Really Unlearned? Verifying Machine Unlearning via Influential Sample Pairs
Authors: Heng Xu, Tianqing Zhu, Lefeng Zhang, Wanlei Zhou | Published: 2024-06-16
Adversarial Machine Unlearning
Authors: Zonglin Di, Sixie Yu, Yevgeniy Vorobeychik, Yang Liu | Published: 2024-06-11
LLM Dataset Inference: Did you train on my dataset?
Authors: Pratyush Maini, Hengrui Jia, Nicolas Papernot, Adam Dziedzic | Published: 2024-06-10
A Survey on Machine Unlearning: Techniques and New Emerged Privacy Risks
Authors: Hengzhu Liu, Ping Xiong, Tianqing Zhu, Philip S. Yu | Published: 2024-06-10
Model for Peanuts: Hijacking ML Models without Training Access is Possible
Authors: Mahmoud Ghorbel, Halima Bouzidi, Ioan Marius Bilasco, Ihsen Alouani | Published: 2024-06-03
Lost in the Averages: A New Specific Setup to Evaluate Membership Inference Attacks Against Machine Learning Models
Authors: Florent Guépin, Nataša Krčo, Matthieu Meeus, Yves-Alexandre de Montjoye | Published: 2024-05-24
Tighter Privacy Auditing of DP-SGD in the Hidden State Threat Model
Authors: Tudor Cebere, Aurélien Bellet, Nicolas Papernot | Published: 2024-05-23 | Updated: 2024-10-14