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Statistical Measurement of Information Leakage

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If you have a question about this talk, please contact Dan Ghica.

Information theory provides a range of useful methods to analyse probability distributions and sampled data. A number of authors have shown how these techniques can be applied to measure information flow and the loss of anonymity in secure systems. However, all this work has assumed that the exact probabilities of every action are known, or that the system is completely non-deterministic. In this talk, I will describe how it’s possible to measures of information leakage based on mutual information and capacity can be calculated, automatically, from trial runs of a system alone. We find a confidence interval for this estimate based on the number of possible inputs, observations and samples. We have developed a tool to automatically perform this analysis and we demonstrate this tool by analysing a Mixminon anonymous remailer node.

Joint work with Konstantinos Chatzikokolakis and Apratim Guha, I will be presenting this work at TACAS next month.

This talk is part of the Lab Lunch series.

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