We study privacy-preserving query answering in Description Logics (DLs). Specifically, we consider the approach of controlled query evaluation (CQE) based on the notion of instance indistinguishability. We derive data complexity results for query answering over DL-LiteR ontologies, through a comparison with an alternative, existing confidentiality-preserving approach to CQE. Finally, we identify a semantically well-founded notion of approximated query answering for CQE, and prove that, for DL-LiteR ontologies, this form of CQE is tractable with respect to data complexity and is first-order rewritable, i.e., it is always reducible to the evaluation of a first-order query over the data instance.
2020, Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, Pages 1791-1797
Controlled Query Evaluation in Description Logics Through Instance Indistinguishability (04b Atto di convegno in volume)
Cima Gianluca, Lembo Domenico, Rosati Riccardo, Fabio Savo Domenico
Gruppo di ricerca: Artificial Intelligence and Knowledge Representation, Gruppo di ricerca: Data Management and Semantic Technologies