978 citations · 1.2k across the 16 of their papers we have counts for
8 papers · 1 filter
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…
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…
Privacy by design in big data: An overview of privacy enhancing technologies in the era of big data analytics
Giuseppe D'Acquisto, Josep Domingo-Ferrer, Panayiotis Kikiras +3
The extensive collection and processing of personal information in big data analytics has given rise to serious privacy concerns, related to wide scale electronic surveillance, pro…