collaborators

5 papers

cs.IT2026

Information Density Bounds for Privacy

Sara Saeidian, Leonhard Grosse, Parastoo Sadeghi +2

This paper explores the implications of guaranteeing privacy by imposing a lower bound on the information density between the private and the public data. We introduce a novel and…

cs.IT2026

Sparse Point-wise Privacy Leakage: Mechanism Design and Fundamental Limits

Amirreza Zamani, Sajad Daei, Parastoo Sadeghi +1

We study an information-theoretic privacy mechanism design problem, where an agent observes useful data that is arbitrarily correlated with sensitive data , and design discl…

cs.IT2026

Privacy-Utility Trade-offs Under Multi-Level Point-Wise Leakage Constraints

Amirreza Zamani, Parastoo Sadeghi, Mikael Skoglund

An information-theoretic privacy mechanism design is studied, where an agent observes useful data which is correlated with the private data . The agent wants to reveal the i…

cs.IT2025

An Extension of the Adversarial Threat Model in Quantitative Information Flow

Mohammad Amin Zarrabian, Parastoo Sadeghi

In this paper, we propose an extended framework for quantitative information flow (QIF), aligned with the previously proposed core-concave generalization of entropy measures, to in…

cs.IT2025

An Information Geometric Approach to Local Information Privacy with Applications to Max-lift and Local Differential Privacy

Amirreza Zamani, Parastoo Sadeghi, Mikael Skoglund

We study an information-theoretic privacy mechanism design, where an agent observes useful data and wants to reveal the information to a user. Since the useful data is correlat…