Quantifying Information Leakage in Finite Order Deterministic Programs

Information flow analysis is a powerful technique for reasoning about the sensitive information exposed by a program during its execution. While past work has proposed information theoretic metrics (e.g., Shannon entropy, min-entropy, guessing entropy, etc.) to quantify such information leakage, we argue that some of these measures not only result in counter-intuitive measures of leakage, but also are inherently prone to conflicts when comparing two programs P₁ and P₂ - say Shannon entropy predicts higher leakage for program P₁, while guessing entropy predicts higher leakage for program P₂. This paper presents the first attempt towards addressing such conflicts and derives solutions for conflict-free comparison of finite order deterministic programs.