Quantifying Information Flow for Dynamic Secrets (extended version). Piotr Mardziel, Mario Alvim, Michael Hicks, and Michael Clarkson. Technical Report CS-TR-5035, Department of Computer Science, the University of Maryland, College Park, May 2014.

A metric is proposed for quantifying leakage of information about secrets and about how secrets change over time. The metric is used with a model of information flow for probabilistic, interactive systems with adaptive adversaries. The model and metric are implemented in a probabilistic programming language and used to analyze several examples. The analysis demonstrates that adaptivity increases the amount of information that adversaries learn.

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@TECHREPORT{mardziel14timeTR,
  AUTHOR = {Piotr Mardziel and Mario Alvim and Michael Hicks and Michael Clarkson},
  TITLE = {Quantifying Information Flow for Dynamic Secrets (extended version)},
  INSTITUTION = {Department of Computer Science, the University of Maryland, College Park},
  NUMBER = {CS-TR-5035},
  MONTH = MAY,
  YEAR = 2014
}

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