11 papers
Goodbye Equal Error Rate, Hello Local Information Disclosure: Evaluating Voice Anonymisation against 1-to-N Linkage Threats
DÄvis Å terns, Konstantinos Drossos, Natasha Fernandes +2
Voice anonymisation aims to protect speaker identity. Currently, its empirical privacy evaluation heavily relies on the Equal Error Rate (EER). Originally designed for biometric ve…
Minimal Effort to Consensus (MEC) polarization measure
Jesús Aranda, Juan Francisco DÃaz, Juan Camilo Narváez +4
We introduce the Minimum Effort to Consensus (MEC), a measure that quantifies polarization as resistance to consensus: a population is highly polarized when much effort is needed t…
Information Leakage Envelopes
Sara Saeidian, Carlos Pinzón, Catuscia Palamidessi
We study privacy guarantees in the framework of pointwise maximal leakage (PML) that satisfy two requirements: they are robust under post-processing and upper bound the failure pro…
Protection against Source Inference Attacks in Federated Learning
Andreas Athanasiou, Kangsoo Jung, Catuscia Palamidessi
Federated Learning (FL) was initially proposed as a privacy-preserving machine learning paradigm. However, FL has been shown to be susceptible to a series of privacy attacks. Recen…
Estimating the True Distribution of Data Collected with Randomized Response
Carlos Antonio Pinzón, Ehab ElSalamouny, Lucas Massot +3
Randomized Response (RR) is a protocol designed to collect and analyze categorical data with local differential privacy guarantees. It has been used as a building block of mechanis…
Experiments \& Analysis of Privacy-Preserving SQL Query Sanitization Systems
Loïs Ecoffet, Veronika Rehn-Sonigo, Jean-François Couchot +1
Analytical SQL queries are essential for extracting insights from relational databases but concurrently introduce significant privacy risks by potentially exposing sensitive inform…