Studying Maximum Information Leakage Using Karush-Kuhn-Tucker Conditions

TL;DR

This paper presents a general method for determining the maximum information leakage in programs and protocols by combining information theory with KKT conditions, applicable to practical scenarios.

Contribution

It introduces a novel approach that integrates information theory and optimization techniques to solve the channel capacity problem for information leakage.

Findings

Provides a general solution to maximum information leakage problem.

Demonstrates applicability to practical programs and protocols.

Generalizes previous methods in the field.

Abstract

When studying the information leakage in programs or protocols, a natural question arises: "what is the worst case scenario?". This problem of identifying the maximal leakage can be seen as a channel capacity problem in the information theoretical sense. In this paper, by combining two powerful theories: Information Theory and Karush-Kuhn-Tucker conditions, we demonstrate a very general solution to the channel capacity problem. Examples are given to show how our solution can be applied to practical contexts of programs and anonymity protocols, and how this solution generalizes previous approaches to this problem.