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Quantifying Information Flow with Beliefs

dc.contributor.authorClarkson, Michael R.en_US
dc.contributor.authorMyers, Andrew C.en_US
dc.contributor.authorSchneider, Fred B.en_US
dc.date.accessioned2007-04-04T20:47:45Z
dc.date.available2007-04-04T20:47:45Z
dc.date.issued2007-03-01en_US
dc.description.abstractTo 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.en_US
dc.format.extent319834 bytes
dc.format.mimetypeapplication/pdf
dc.identifier.citationhttp://techreports.library.cornell.edu:8081/Dienst/UI/1.0/Display/cul.cis/TR2007-2075en_US
dc.identifier.urihttps://hdl.handle.net/1813/5766
dc.language.isoen_USen_US
dc.publisherCornell Universityen_US
dc.subjectcomputer scienceen_US
dc.subjecttechnical reporten_US
dc.titleQuantifying Information Flow with Beliefsen_US
dc.typetechnical reporten_US

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