Task-Structured Probabilistic I/O Automata
Author(s)
Canetti, Ran
Cheung, Ling
Kaynar, Dilsun
Liskov, Moses
Lynch, Nancy A.
Pereira, Olivier
Segala, Roberto
Advisor(s)
Nancy Lynch
Date Issued
March 31, 2006
Series/Report no.
Massachusetts Institute of Technology Computer Science and Artificial Intelligence Laboratory
Abstract
In 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.
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