Information-Theoretic Approaches to Differential Privacy

TL;DR

This tutorial explores how information-theoretic measures like mutual information and divergence can interpret and analyze differential privacy, offering new insights into privacy guarantees across different systems.

Contribution

It provides a comprehensive summary of existing literature connecting differential privacy with information-theoretic concepts, enhancing understanding of privacy guarantees.

Findings

Information-theoretic measures offer new interpretations of differential privacy.

Connections between privacy guarantees and information measures are systematically analyzed.

The tutorial summarizes key literature linking differential privacy with information theory.

Abstract

This tutorial studies relationships between differential privacy and various information-theoretic measures by using several selective articles. In particular, we present how these connections can provide new interpretations for the privacy guarantee in systems that deploy differential privacy in an information-theoretic framework. To this end, the tutorial provides an extensive summary on the existing literature that makes use of information-theoretic measures and tools such as mutual information, min-entropy, Kullback-Leibler divergence and rate-distortion function for quantification and characterization of differential privacy in various settings.