978 citations · 1.2k across the 16 of their papers we have counts for
4 papers · 1 filter
Did the Neurons Read your Book? Document-level Membership Inference for Large Language Models
Matthieu Meeus, Shubham Jain, Marek Rei +1
With large language models (LLMs) poised to become embedded in our daily lives, questions are starting to be raised about the data they learned from. These questions range from pot…
Synthetic is all you need: removing the auxiliary data assumption for membership inference attacks against synthetic data
Florent Guépin, Matthieu Meeus, Ana-Maria Cretu +1
Synthetic data is emerging as one of the most promising solutions to share individual-level data while safeguarding privacy. While membership inference attacks (MIAs), based on sha…
Achilles' Heels: Vulnerable Record Identification in Synthetic Data Publishing
Matthieu Meeus, Florent Guépin, Ana-Maria Cretu +1
Synthetic data is seen as the most promising solution to share individual-level data while preserving privacy. Shadow modeling-based Membership Inference Attacks (MIAs) have become…
Investigating the Effect of Misalignment on Membership Privacy in the White-box Setting
Ana-Maria Cretu, Daniel Jones, Yves-Alexandre de Montjoye +1
Machine learning models have been shown to leak sensitive information about their training datasets. Models are increasingly deployed on devices, raising concerns that white-box ac…