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Refinement Metrics for Quantitative Information Flow

  • Konstantinos ChatzikokolakisEmail author
  • Geoffrey Smith
Chapter
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11760)

Abstract

In Quantitative Information Flow, refinement ( Open image in new window ) expresses the strong property that one channel never leaks more than another. Since two channels are then typically incomparable, here we explore a family of refinement quasimetrics offering greater flexibility. We show these quasimetrics let us unify refinement and capacity, we show that some of them can be computed efficiently via linear programming, and we establish upper bounds via the Earth Mover’s distance. We illustrate our techniques on the Crowds protocol.

Supplementary material

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.University of AthensAthensGreece
  2. 2.Florida International UniversityMiamiUSA

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