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

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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

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To cite the version in the repository, please use this identifier: https://doi.org/10.15488/3464

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Sum total of downloads: 245




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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.
License of this version: Es gilt deutsches Urheberrecht. Das Dokument darf zum eigenen Gebrauch kostenfrei genutzt, aber nicht im Internet bereitgestellt oder an Außenstehende weitergegeben werden.
Document Type: conferenceObject
Publishing status: acceptedVersion
Issue Date: 2018
Appears in Collections:Fakultät für Elektrotechnik und Informatik

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pos. country downloads
total perc.
1 image of flag of Germany Germany 120 48.98%
2 image of flag of France France 22 8.98%
3 image of flag of United States United States 16 6.53%
4 image of flag of Austria Austria 13 5.31%
5 image of flag of Spain Spain 9 3.67%
6 image of flag of Algeria Algeria 6 2.45%
7 image of flag of China China 6 2.45%
8 image of flag of Canada Canada 6 2.45%
9 image of flag of Belgium Belgium 5 2.04%
10 image of flag of Mexico Mexico 4 1.63%
    other countries 38 15.51%

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