Journal
2012 IEEE 25TH COMPUTER SECURITY FOUNDATIONS SYMPOSIUM (CSF)
Volume -, Issue -, Pages 265-279Publisher
IEEE
DOI: 10.1109/CSF.2012.26
Keywords
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Funding
- MURI program under AFOSR [FA9550-08-1-0352]
- INRIA
- LIX
- National Science Foundation [CNS-1116318, CNS-0831114]
- Digiteo
- Direct For Computer & Info Scie & Enginr
- Division Of Computer and Network Systems [1116318] Funding Source: National Science Foundation
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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, C-1 and C-2, and the possibility of factoring C-1 into C2C3, for some C-3. Based on this connection, we propose a generalization of the Lattice of Information from deterministic to probabilistic channels.
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