29 citations · 129 across the 19 of their papers we have counts for
5 papers · 1 filter
On the Impact of Multi-dimensional Local Differential Privacy on Fairness
Karima Makhlouf, Heber H. Arcolezi, Sami Zhioua +2
Automated decision systems are increasingly used to make consequential decisions in people's lives. Due to the sensitivity of the manipulated data as well as the resulting decision…
Causal Discovery Under Local Privacy
Rūta Binkytė, Carlos Pinzón, Szilvia Lestyán +3
Differential privacy is a widely adopted framework designed to safeguard the sensitive information of data providers within a data set. It is based on the application of controlled…
Revealing the True Cost of Locally Differentially Private Protocols: An Auditing Perspective
Héber H. Arcolezi, Sébastien Gambs
While the existing literature on Differential Privacy (DP) auditing predominantly focuses on the centralized model (e.g., in auditing the DP-SGD algorithm), we advocate for extendi…
On the Utility Gain of Iterative Bayesian Update for Locally Differentially Private Mechanisms
Héber H. Arcolezi, Selene Cerna, Catuscia Palamidessi
This paper investigates the utility gain of using Iterative Bayesian Update (IBU) for private discrete distribution estimation using data obfuscated with Locally Differentially Pri…
(Local) Differential Privacy has NO Disparate Impact on Fairness
Héber H. Arcolezi, Karima Makhlouf, Catuscia Palamidessi
In recent years, Local Differential Privacy (LDP), a robust privacy-preserving methodology, has gained widespread adoption in real-world applications. With LDP, users can perturb t…