5 papers
Sparse Discrete Laplace and Gaussian Mechanisms under Local Differential Privacy
Amirreza Zamani, Sajad Daei, Parastoo Sadeghi +1
We study sparse locally private channels of the form where the admissible output set is allowed to depend on the private input …
How Entanglement Reshapes the Geometry of Quantum Differential Privacy
Xi Wang, Parastoo Sadeghi, Guodong Shi
Quantum differential privacy provides a rigorous framework for quantifying privacy guarantees in quantum information processing. While classical correlations are typically regarded…
Composition Theorems for f-Differential Privacy
Natasha Fernandes, Annabelle McIver, Parastoo Sadeghi
"f differential privacy" (fDP) is a recent definition for privacy privacy which can offer improved predictions of "privacy loss". It has been used to analyse specific privacy mecha…
Comparing privacy notions for protection against reconstruction attacks in machine learning
Sayan Biswas, Mark Dras, Pedro Faustini +4
Within the machine learning community, reconstruction attacks are a principal concern and have been identified even in federated learning (FL), which was designed with privacy pres…
Bayes' capacity as a measure for reconstruction attacks in federated learning
Sayan Biswas, Mark Dras, Pedro Faustini +4
Within the machine learning community, reconstruction attacks are a principal attack of concern and have been identified even in federated learning, which was designed with privacy…