BOUNCER: Privacy-aware Query Processing Over Federations of RDF Datasets

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dc.identifier.uri http://dx.doi.org/10.15488/3464
dc.identifier.uri http://www.repo.uni-hannover.de/handle/123456789/3494
dc.contributor.author Endris, Kemele M ger
dc.contributor.author Almhithawi, Zuhair ger
dc.contributor.author Lytra, Ioanna ger
dc.contributor.author Vidal, Maria-Esther ger
dc.contributor.author Auer, Sören ger
dc.date.accessioned 2018-06-11T09:00:38Z
dc.date.available 2018-06-11T09:00:38Z
dc.date.issued 2018
dc.identifier.citation Endris, K.M.; Almhithawi, Z.; Lytra, I.; Vidal, M.-E.; Auer, S.: BOUNCER: Privacy-aware Query Processing Over Federations of RDF Datasets. DEXA 2018, 3-6 September 2018, Regensburg, Germany. http://www.dexa.org/dexa2018 ger
dc.description.abstract Data provides the basis for emerging scientific and interdisciplinary data-centric applications with the potential of improving the quality of life for the citizens. However, effective data-centric applications demand data management techniques able to process a large volume of data which may include sensitive data, e.g., financial transactions, medical procedures, or personal data. Managing sensitive data requires the enforcement of privacy and access control regulations, particularly, during the execution of queries against datasets that include sensitive and nonsensitive data. In this paper, we tackle the problem of enforcing privacy regulations during query processing, and propose BOUNCER, a privacy-aware query engine over federations of RDF datasets. BOUNCER allows for the description of RDF datasets in terms of RDF molecule templates, i.e., abstract descriptions of the properties of the entities in an RDF dataset and their privacy regulations. Furthermore, BOUNCER implements query decomposition and optimization techniques able to identify query plans over RDF datasets that not only contain the relevant entities to answer a query, but that are also regulated by policies that allow for accessing these relevant entities. We empirically evaluate the effectiveness of the BOUNCER privacy-aware techniques over state-of-the-art benchmarks of RDF datasets. The observed results suggest that BOUNCER can effectively enforce access control regulations at different granularity without impacting the performance of query processing. ger
dc.language.iso eng ger
dc.publisher Heidelberg : Springer
dc.rights Es gilt deutsches Urheberrecht. Das Dokument darf zum eigenen Gebrauch kostenfrei genutzt, aber nicht im Internet bereitgestellt oder an Außenstehende weitergegeben werden. ger
dc.subject Federated Engine eng
dc.subject Access-control eng
dc.subject Semantic Web eng
dc.subject Linked Data eng
dc.subject.ddc 004 | Informatik ger
dc.title BOUNCER: Privacy-aware Query Processing Over Federations of RDF Datasets eng
dc.type conferenceObject ger
dc.type Text ger
dc.description.version acceptedVersion ger
tib.accessRights frei zug�nglich ger


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