Abstract
Database sanitization allows to share and publish open (linked) data without jeopardizing privacy. During their sanitization, graph databases are transformed following graph transformations that are usually described informally or through ad-hoc processes.
This paper is a first effort toward bridging the gap between the rigorous graph rewriting approaches and graph sanitization by providing basic generic graph rewriting operators to serve as a basis for the construction of sanitization mechanisms. As a proof of concept, we formalize two operators, blank node creation and weighted relation randomization, using an algebraic graph rewriting approach that takes into account semantic through the equivalent of Where and Except clauses. We show that these operators can be used to achieve pseudonymity and local differential privacy. Both operators and all related rewriting rules are implemented using the Attributed Graph Grammar System (AGG), providing a concrete tool implementing formal graph rewriting mechanisms to sanitize semantic graph databases.
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Boiret, A., Eichler, C., Nguyen, B. (2022). Privacy Operators for Semantic Graph Databases as Graph Rewriting. In: Chiusano, S., et al. New Trends in Database and Information Systems. ADBIS 2022. Communications in Computer and Information Science, vol 1652. Springer, Cham. https://doi.org/10.1007/978-3-031-15743-1_34
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DOI: https://doi.org/10.1007/978-3-031-15743-1_34
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