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dc.contributor.advisorNancy Lynch
dc.contributor.authorCanetti, Ran
dc.contributor.authorCheung, Ling
dc.contributor.authorKaynar, Dilsun
dc.contributor.authorLiskov, Moses
dc.contributor.authorLynch, Nancy
dc.contributor.authorPereira, Olivier
dc.contributor.authorSegala, Roberto
dc.contributor.otherTheory of Computation
dc.date.accessioned2006-03-31T17:51:50Z
dc.date.available2006-03-31T17:51:50Z
dc.date.issued2006-03-31
dc.identifier.otherMIT-CSAIL-TR-2006-023
dc.identifier.urihttp://hdl.handle.net/1721.1/32525
dc.description.abstractIn the Probabilistic I/O Automata (PIOA) framework, nondeterministicchoices are resolved using perfect-information schedulers,which are similar to history-dependent policies for Markov decision processes(MDPs). These schedulers are too powerful in the setting of securityanalysis, leading to unrealistic adversarial behaviors. Therefore, weintroduce in this paper a novel mechanism of task partitions for PIOAs.This allows us to define partial-information adversaries in a systematicmanner, namely, via sequences of tasks.The resulting task-PIOA framework comes with simple notions of externalbehavior and implementation, and supports simple compositionalityresults. A new type of simulation relation is defined and proven soundwith respect to our notion of implementation. To illustrate the potentialof this framework, we summarize our verification of an ObliviousTransfer protocol, where we combine formal and computational analyses.Finally, we present an extension with extra expressive power, usinglocal schedulers of individual components.
dc.format.extent45 p.
dc.format.extent2404679 bytes
dc.format.extent487620 bytes
dc.format.mimetypeapplication/postscript
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.relation.ispartofseriesMassachusetts Institute of Technology Computer Science and Artificial Intelligence Laboratory
dc.relation.isreplacedbyhttp://hdl.handle.net/1721.1/33964
dc.relation.urihttp://hdl.handle.net/1721.1/33964
dc.titleTask-Structured Probabilistic I/O Automata


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