14 citations · 37 across the 10 of their papers we have counts for
9 papers · 1 filter
Evaluating Concept Filtering Defenses against Child Sexual Abuse Material Generation by Text-to-Image Models
Ana-Maria Cretu, Klim Kireev, Amro Abdalla +5
We evaluate the effectiveness of filtering child images from training datasets of text-to-image models to prevent model misuse to create child sexual abuse material (CSAM). First,…
QueryCheetah: Fast Automated Discovery of Attribute Inference Attacks Against Query-Based Systems
Bozhidar Stevanoski, Ana-Maria Cretu, Yves-Alexandre de Montjoye
Query-based systems (QBSs) are one of the key approaches for sharing data. QBSs allow analysts to request aggregate information from a private protected dataset. Attacks are a cruc…
A Zero Auxiliary Knowledge Membership Inference Attack on Aggregate Location Data
Vincent Guan, Florent Guépin, Ana-Maria Cretu +1
Location data is frequently collected from populations and shared in aggregate form to guide policy and decision making. However, the prevalence of aggregated data also raises the…
Re-pseudonymization Strategies for Smart Meter Data Are Not Robust to Deep Learning Profiling Attacks
Ana-Maria Cretu, Miruna Rusu, Yves-Alexandre de Montjoye
Smart meters, devices measuring the electricity and gas consumption of a household, are currently being deployed at a fast rate throughout the world. The data they collect are extr…
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…
Deep perceptual hashing algorithms with hidden dual purpose: when client-side scanning does facial recognition
Shubham Jain, Ana-Maria Cretu, Antoine Cully +1
End-to-end encryption (E2EE) provides strong technical protections to individuals from interferences. Governments and law enforcement agencies around the world have however raised…
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…
QuerySnout: Automating the Discovery of Attribute Inference Attacks against Query-Based Systems
Ana-Maria Cretu, Florimond Houssiau, Antoine Cully +1
Although query-based systems (QBS) have become one of the main solutions to share data anonymously, building QBSes that robustly protect the privacy of individuals contributing to…