TGC 2012: Trustworthy Global Computing pp 198-212 | Cite as
Modular Reasoning about Differential Privacy in a Probabilistic Process Calculus
Conference paper
Abstract
The verification of systems for protecting sensitive and confidential information is becoming an increasingly important issue. Differential privacy is a promising notion of privacy originated from the community of statistical databases, and now widely adopted in various models of computation. We consider a probabilistic process calculus as a specification formalism for concurrent systems, and we propose a framework for reasoning about the degree of differential privacy provided by such systems. In particular, we investigate the preservation of the degree of privacy under composition via the various operators. We illustrate our idea by proving an anonymity-preservation property for a variant of the Crowds protocol for which the standard analyses from the literature are inapplicable. Finally, we make some preliminary steps towards automatically computing the degree of privacy of a system in a compositional way.
Keywords
Probabilistic Choice Parallel Composition Adjacency Relation Differential Privacy Nondeterministic Choice
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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