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We study an information theoretic privacy mechanism design problem for two scenarios where the private data is either observable or hidden. In each scenario, we first consider bounded mutual information as privacy leakage criterion, then we…

Information Theory · Computer Science 2022-12-26 Amirreza Zamani , Tobias J. Oechtering , Mikael Skoglund

The design of privacy mechanisms for two scenarios is studied where the private data is hidden or observable. In the first scenario, an agent observes useful data $Y$, which is correlated with private data $X$, and wants to disclose the…

Information Theory · Computer Science 2023-01-16 Amirreza Zamani , Tobias J. Oechtering , Mikael Skoglund

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

An information-theoretic privacy mechanism design is studied, where an agent observes useful data $Y$ which is correlated with the private data $X$. The agent wants to reveal the information to a user, hence, the agent utilizes a privacy…

Information Theory · Computer Science 2026-01-09 Amirreza Zamani , Parastoo Sadeghi , Mikael Skoglund

The design of a statistical signal processing privacy problem is studied where the private data is assumed to be observable. In this work, an agent observes useful data $Y$, which is correlated with private data $X$, and wants to disclose…

Information Theory · Computer Science 2023-09-19 Amirreza Zamani , Tobias J. Oechtering , Mikael Skoglund

We study a statistical signal processing privacy problem, where an agent observes useful data $Y$ and wants to reveal the information to a user. Since the useful data is correlated with the private data $X$, the agent employs a privacy…

Information Theory · Computer Science 2021-07-16 Amirreza Zamani , Tobias J. Oechtering , Mikael Skoglund

We study an information-theoretic privacy mechanism design, where an agent observes useful data $Y$ and wants to reveal the information to a user. Since the useful data is correlated with the private data $X$, the agent uses a privacy…

Information Theory · Computer Science 2025-01-22 Amirreza Zamani , Parastoo Sadeghi , Mikael Skoglund

In traditional mechanism design, agents only care about the utility they derive from the outcome of the mechanism. We look at a richer model where agents also assign non-negative dis-utility to the information about their private types…

Computer Science and Game Theory · Computer Science 2015-03-19 Kobbi Nissim , Claudio Orlandi , Rann Smorodinsky

Consider a pair of random variables $(X,Y)$ distributed according to a given joint distribution $p_{XY}$. A curator wishes to maximally disclose information about $Y$, while limiting the information leakage incurred on $X$. Adopting mutual…

Information Theory · Computer Science 2023-01-30 Borzoo Rassouli , Deniz Gündüz

A scheme that publishes aggregate information about sensitive data must resolve the trade-off between utility to information consumers and privacy of the database participants. Differential privacy is a well-established definition of…

Cryptography and Security · Computer Science 2010-01-18 Mangesh Gupte , Mukund Sundararajan

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

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

A mechanism for releasing information about a statistical database with sensitive data must resolve a trade-off between utility and privacy. Privacy can be rigorously quantified using the framework of {\em differential privacy}, which…

Databases · Computer Science 2009-03-20 Arpita Ghosh , Tim Roughgarden , Mukund Sundararajan

In this paper, we study a stochastic disclosure control problem using information-theoretic methods. The useful data to be disclosed depend on private data that should be protected. Thus, we design a privacy mechanism to produce new data…

Information Theory · Computer Science 2021-03-24 Amirreza Zamani , Tobias J. Oechtering , Mikael Skoglund

Each agent in a network makes a local observation that is linearly related to a set of public and private parameters. The agents send their observations to a fusion center to allow it to estimate the public parameters. To prevent leakage of…

Systems and Control · Electrical Eng. & Systems 2020-08-12 Chong Xiao Wang , Yang Song , Wee Peng Tay

Consider a data publishing setting for a data set with public and private features. The objective of the publisher is to maximize the amount of information about the public features in a revealed data set, while keeping the information…

Information Theory · Computer Science 2018-05-11 Hao Wang , Mario Diaz , Flavio P. Calmon , Lalitha Sankar

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

Due to the recent popularity of online social networks, coupled with people's propensity to disclose personal information in an effort to achieve certain gratifications, the problem of navigating the tradeoff between privacy and utility…

Information Theory · Computer Science 2020-03-12 Chandra Sharma , George Amariucai

Large language models (LLMs) and AI agents are increasingly integrated into enterprise systems to access internal databases and generate context-aware responses. While such integration improves productivity and decision support, the model…

Cryptography and Security · Computer Science 2026-03-19 Ya-Ting Yang , Quanyan Zhu

This paper is a survey of recent work at the intersection of mechanism design and privacy. The connection is a natural one, but its study has been jump-started in recent years by the advent of differential privacy, which provides a…

Computer Science and Game Theory · Computer Science 2013-06-11 Mallesh Pai , Aaron Roth
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