Skip to main content
Article thumbnail
Location of Repository

2012 IEEE 25th Computer Security Foundations Symposium Measuring Information Leakage using Generalized Gain Functions

By Mário S. Alvim, Kostas Chatzikokolakis, Catuscia Palamidessi and Geoffrey Smith

Abstract

Abstract—This paper introduces g-leakage, a rich generalization of the min-entropy model of quantitative information flow. In g-leakage, the benefit that an adversary derives from a certain guess about a secret is specified using a gain function g. Gain functions allow a wide variety of operational scenarios to be modeled, including those where the adversary benefits from guessing a value close to the secret, guessing a part of the secret, guessing a property of the secret, or guessing the secret within some number of tries. We prove important properties of g-leakage, including bounds between min-capacity, g-capacity, and Shannon capacity. We also show a deep connection between a strong leakage ordering on two channels, C1 and C2, and the possibility of factoring C1 into C2C3, for some C3. Based on this connection, we propose a generalization of the Lattice of Information from deterministic to probabilistic channels. I

Year: 2013
OAI identifier: oai:CiteSeerX.psu:10.1.1.353.1797
Provided by: CiteSeerX
Download PDF:
Sorry, we are unable to provide the full text but you may find it at the following location(s):
  • http://citeseerx.ist.psu.edu/v... (external link)
  • http://users.cis.fiu.edu/~smit... (external link)
  • Suggested articles


    To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.