Computer Science – Cryptography and Security
Scientific paper
2010-09-20
Computer Science
Cryptography and Security
14 pages, 1 figure. A shorter version of this paper is submitted to ICC 2011
Scientific paper
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.
Srivatsa Mudhakar
Zhu Jia-Ji
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