Generalized bisimulation metrics

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The bisimilarity pseudometric based on the Kantorovich lifting is one of the most popular metrics for probabilistic processes proposed in the literature. However, its application in verification is limited to linear properties. We propose a generalization of this metric which allows to deal with a wider class of properties, such as those used in security and privacy. More precisely, we propose a family of metrics, parametrized on a notion of distance which depends on the property we want to verify. Furthermore, we show that the members of this family still characterize bisimilarity in terms of their kernel, and provide a bound on the corresponding metrics on traces. Finally, we study the case of a metric corresponding to differential privacy. We show that in this case it is possible to have a dual form, easier to compute, and we prove that the typical constructs of process algebra are non-expansive with respect to this metrics, thus paving the way to a modular approach to verification.

Original languageEnglish
Title of host publicationConcurrency Theory - 25th International Conference, CONCUR 2014, Proceedings
PublisherSpringer Verlag
Pages32-46
Number of pages15
ISBN (Print)9783662445839
DOIs
Publication statusPublished - 1 Jan 2014
Event25th International Conference on Concurrency Theory, CONCUR 2014 - Rome, Italy
Duration: 2 Sept 20145 Sept 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8704 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference25th International Conference on Concurrency Theory, CONCUR 2014
Country/TerritoryItaly
CityRome
Period2/09/145/09/14

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