Hidden-Markov Program Algebra with iteration
Abstract
We use Hidden Markov Models to motivate a quantitative compositional semantics for noninterference-based security with iteration, including a refinement- or "implements" relation that compares two programs with respect to their information leakage; and we propose a program algebra for source-level reasoning about such programs, in particular as a means of establishing that an "implementation" program leaks no more than its "specification" program. <p>This joins two themes: we extend our earlier work, having iteration but only qualitative, by making it quantitative; and we extend our earlier quantitative work by including iteration. <p>We advocate stepwise refinement and source-level program algebra, both as conceptual reasoning tools and as targets for automated assistance. A selection of algebraic laws is given to support this view in the case of quantitative noninterference; and it is demonstrated on a simple iterated password-guessing attack.
Cite
@article{arxiv.1102.0333,
title = {Hidden-Markov Program Algebra with iteration},
author = {Annabelle McIver and Larissa Meinicke and Carroll Morgan},
journal= {arXiv preprint arXiv:1102.0333},
year = {2019}
}