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Please use this identifier to cite or link to this item: http://hdl.handle.net/1813/5766
Title: Quantifying Information Flow with Beliefs
Authors: Clarkson, Michael R.
Myers, Andrew C.
Schneider, Fred B.
Keywords: computer science
technical report
Issue Date: 1-Mar-2007
Publisher: Cornell University
Citation: http://techreports.library.cornell.edu:8081/Dienst/UI/1.0/Display/cul.cis/TR2007-2075
Abstract: To reason about information flow, a new model is developed that describes how attacker beliefs change due to the attacker's observation of the execution of a probabilistic (or deterministic) program. The model enables compositional reasoning about information flow from attacks involving sequences of interactions. The model also supports a new metric for quantitative information flow that measures accuracy of an attacker's beliefs. Applying this new metric reveals inadequacies of traditional information flow metrics, which are based on reduction of uncertainty. However, the new metric is sufficiently general that it can be instantiated to measure either accuracy or uncertainty. The new metric can also be used to reason about misinformation; deterministic programs are shown to be incapable of producing misinformation. Additionally, programs in which nondeterministic choices are made by insiders, who collude with attackers, can be analyzed.
URI: http://hdl.handle.net/1813/5766
Appears in Collections:Computing and Information Science Technical Reports

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