Kgastor: a Privacy By Design Knowledge Graph anonymized Store

Regulations such as GDPR and CCPA are making the management of personal information an increasingly sensitive issue for businesses and organizations. We consider that data protection mechanisms must intervene upstream as recommended by the principles of privacy by design. Our view is that database m...

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Bibliographic Details
Published in2022 IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom) pp. 670 - 679
Main Authors Thouvenot, Maxime, Calvez, Philippe, Cure, Olivier
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.12.2022
Subjects
Data models
Data partitioning
Data privacy
Information filtering
Privacy
Privacy by design
RDF
Resource description framework
Standards organizations
Systems engineering and theory
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Summary:Regulations such as GDPR and CCPA are making the management of personal information an increasingly sensitive issue for businesses and organizations. We consider that data protection mechanisms must intervene upstream as recommended by the principles of privacy by design. Our view is that database management systems should be equipped with anonymization mechanisms. By relying on a partitioned data storage scheme, support for data update operations and query rewriting, our approach offers a trade-off between data privacy and utility. Some advantages of our approach are a low overhead of storing partitioned data, the performance of CRUD operations and the efficiency of a batch delivery approach to data updates. We evaluate our prototype on an open source RDF store and on synthetic datasets.
ISSN:2324-9013
DOI:10.1109/TrustCom56396.2022.00096