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• W2602854785 abstract "Traditional approaches to Quantitative Information Flow QIF represent the adversary's prior knowledge of possible secret values as a single probability distribution. This representation may miss important structure. For instance, representing prior knowledge about passwords of a system's users in this way overlooks the fact that many users generate passwords using some strategy. Knowledge of such strategies can help the adversary in guessing a secret, so ignoring them may underestimate the secret's vulnerability. In this paper we explicitly model strategies as distributions on secrets, and generalize the representation of the adversary's prior knowledge from a distribution on secrets to an environment, which is a distribution on strategies and, thus, a distribution on distributions on secrets, called a hyper-distribution. By applying information-theoretic techniques to environments we derive several meaningful generalizations of the traditional approach to QIF. In particular, we disentangle the vulnerability of a secret from the vulnerability of the strategies that generate secrets, and thereby distinguish security by aggregation--which relies on the uncertainty over strategies--from security by strategy--which relies on the intrinsic uncertainty within a strategy. We also demonstrate that, in a precise way, no further generalization of prior knowledge e.g., by using distributions of even higher order is needed to soundly quantify the vulnerability of the secret." @default.
• W2602854785 created "2017-04-07" @default.
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• W2602854785 date "2017-01-01" @default.
• W2602854785 modified "2023-10-06" @default.
• W2602854785 title "Quantifying Vulnerability of Secret Generation Using Hyper-Distributions" @default.
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• W2602854785 doi "https://doi.org/10.1007/978-3-662-54455-6_2" @default.
• W2602854785 hasPublicationYear "2017" @default.
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