Automatic Discovery and Quantification of Information Leaks

  • Authors:
  • Michael Backes;Boris Kopf;Andrey Rybalchenko

  • Affiliations:
  • -;-;-

  • Venue:
  • SP '09 Proceedings of the 2009 30th IEEE Symposium on Security and Privacy
  • Year:
  • 2009

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Abstract

Information-flow analysis is a powerful technique for reasoning about the sensitive information exposed by a program during its execution. We present the first automatic method for information-flow analysis that discovers what information is leaked and computes its comprehensive quantitative interpretation. The leaked information is characterized by an equivalence relation on secret artifacts, and is represented by a logical assertion over the corresponding program variables. Our measurement procedure computes the number of discovered equivalence classes and their sizes. This provides a basis for computing a set of quantitative properties, which includes all established information-theoretic measures in quantitative information-flow. Our method exploits an inherent connection between formal models of qualitative information-flow and program verification techniques.We provide an implementation of our method that builds upon existing tools for program verification and information-theoretic analysis. Our experimental evaluation indicates the practical applicability of the presented method.