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We introduce and develop a declarative framework for privacypreserving Linked Data publishing in which privacy and utility policies are specified as SPARQL queries. Our approach is data-independent and leads to inspect only the privacy and utility policies in order to determine the sequence of anonymization operations applicable to any graph instance for satisfying the policies. We prove the soundness of our algorithms and gauge their performance through experiments.
Abstract. The Semantic Web technologies include entailment regimes that produce new RDF data from existing ones. In the presence of access control, once a user has legitimately received the answer of a query, she/he can derive new data entailed from the answer that should have been forbidden if carried out inside of the RDF store. In this paper, we define a fine-grained authorization model for which it is possible to check in advance whether such a problem will arise. To this end, we provide a static analysis algorithm which can be used at the time of writing the authorization policy and does not require access to the data. We illustrate the expressiveness of the access control model with several conflict resolution strategies including most specific takes precedence as well as the applicability of the algorithm for diagnosis purposes.
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