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Differential privacy is a notion of privacy that has become very popular in the database community. Roughly, the idea is that a randomized query mechanism provides sufficient privacy protection if the ratio between the probabilities that…

Cryptography and Security · Computer Science 2014-06-18 Mário S. Alvim , Miguel E. Andrés , Konstantinos Chatzikokolakis , Pierpaolo Degano , Catuscia Palamidessi

Consider the problem of storing data in a distributed manner over $T$ servers. Specifically, the data needs to (i) be recoverable from any $\tau$ servers, and (ii) remain private from any $z$ colluding servers, where privacy is quantified…

Information Theory · Computer Science 2024-03-19 Remi A. Chou , Joerg Kliewer

Private Information Retrieval (PIR) is a fundamental problem in the broader fields of security and privacy. In recent years, the problem has garnered significant attention from the research community, leading to achievability schemes and…

Information Theory · Computer Science 2025-02-21 Ningze Wang , Anoosheh Heidarzadeh , Alex Sprintson

In many practical settings, the user needs to retrieve information from a server in a periodic manner, over multiple rounds of communication. In this paper, we discuss the setting in which this information needs to be retrieved privately,…

Information Theory · Computer Science 2019-01-29 Fatemeh Kazemi , Esmaeil Karimi , Anoosheh Heidarzadeh , Alex Sprintson

We consider the total (upload plus download) communication cost of two-database symmetric private information retrieval (SPIR) through its relationship to conditional disclosure of secrets (CDS). In SPIR, a user wishes to retrieve a message…

Information Theory · Computer Science 2022-01-31 Zhusheng Wang , Sennur Ulukus

It is often necessary to disclose training data to the public domain, while protecting privacy of certain sensitive labels. We use information theoretic measures to develop such privacy preserving data disclosure mechanisms. Our mechanism…

Information Theory · Computer Science 2019-04-08 Tianrui Xiao , Ashish Khisti

This paper investigates lift, the likelihood ratio between the posterior and prior belief about sensitive features in a dataset. Maximum and minimum lifts over sensitive features quantify the adversary's knowledge gain and should be bounded…

Information Theory · Computer Science 2023-05-10 Mohammad Amin Zarrabian , Ni Ding , Parastoo Sadeghi

Most methods for publishing data with privacy guarantees introduce randomness into datasets which reduces the utility of the published data. In this paper, we study the privacy-utility tradeoff by taking maximal leakage as the privacy…

Information Theory · Computer Science 2021-05-04 Sara Saeidian , Giulia Cervia , Tobias J. Oechtering , Mikael Skoglund

An attacker can gain information of a user by analyzing its network traffic. The size of transferred data leaks information about the file being transferred or the service being used, and this is particularly revealing when the attacker has…

Cryptography and Security · Computer Science 2022-09-12 Sebastian Simon , Cezara Petrui , Carlos Pinzón , Catuscia Palamidessi

The privacy-utility tradeoff problem is formulated as determining the privacy mechanism (random mapping) that minimizes the mutual information (a metric for privacy leakage) between the private features of the original dataset and a…

Information Theory · Computer Science 2026-05-12 Kousha Kalantari , Oliver Kosut , Lalitha Sankar

Side channels represent a broad class of security vulnerabilities that have been demonstrated to exist in many applications. Because completely eliminating side channels often leads to prohibitively high overhead, there is a need for a…

Information Theory · Computer Science 2020-04-20 Benjamin Wu , Aaron B. Wagner , G. Edward Suh

An information theoretic privacy mechanism design problem for two scenarios is studied where the private data is either hidden or observable. In each scenario, privacy leakage constraints are considered using two different measures. In…

Information Theory · Computer Science 2022-05-11 Amirreza Zamani , Tobias J. Oechtering , Mikael Skoglund

We study the problem of private set intersection (PSI). In this problem, there are two entities $E_i$, for $i=1, 2$, each storing a set $\mathcal{P}_i$, whose elements are picked from a finite field $\mathbb{F}_K$, on $N_i$ replicated and…

Information Theory · Computer Science 2020-12-01 Zhusheng Wang , Karim Banawan , Sennur Ulukus

We investigate the problem of semantic private information retrieval (semantic PIR). In semantic PIR, a user retrieves a message out of $K$ independent messages stored in $N$ replicated and non-colluding databases without revealing the…

Information Theory · Computer Science 2020-03-31 Sajani Vithana , Karim Banawan , Sennur Ulukus

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 operationally meaningful privacy measure called pointwise…

Information Theory · Computer Science 2026-03-17 Sara Saeidian , Leonhard Grosse , Parastoo Sadeghi , Mikael Skoglund , Tobias J. Oechtering

Private information retrieval (PIR) is a mechanism for efficiently downloading messages while keeping the index of the desired message secret from the servers. PIR schemes have been extended to various scenarios with adversarial servers:…

Information Theory · Computer Science 2026-01-23 Atsushi Miki , Toshiyasu Matsushima

We consider the problem of designing a Private Information Retrieval (PIR) scheme on $m$ files replicated on $k$ servers that can collude or, even worse, can return incorrect answers. Our goal is to correctly retrieve a specific message…

Information Theory · Computer Science 2023-05-08 Stanislav Kruglik , Son Hoang Dau , Han Mao Kiah , Huaxiong Wang

We examine the relationship between privacy metrics that utilize information density to measure information leakage between a private and a disclosed random variable. Firstly, we prove that bounding the information density from above or…

Information Theory · Computer Science 2024-02-21 Leonhard Grosse , Sara Saeidian , Parastoo Sadeghi , Tobias J. Oechtering , Mikael Skoglund

We study privacy-utility trade-offs where users share privacy-correlated useful information with a service provider to obtain some utility. The service provider is adversarial in the sense that it can infer the users' private information…

Information Theory · Computer Science 2021-06-29 Xiaoming Duan , Zhe Xu , Rui Yan , Ufuk Topcu

In the conventional robust $T$-colluding private information retrieval (PIR) system, the user needs to retrieve one of the possible messages while keeping the identity of the requested message private from any $T$ colluding servers.…

Information Theory · Computer Science 2021-12-13 Ruida Zhou , Chao Tian , Hua Sun , James Plank
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