We adapt existing approaches for privacy-preserving publishing of linked data to a setting where the data are given as Description Logic (DL) ABoxes with possibly anonymised (formally: existentially quantified) individuals and the privacy policies are expressed using sets of concepts of the DL. We provide a chacterization of compliance of such ABoxes w.r.t. policies, and show how optimal compliant anonymisations of ABoxes that are non-compliant can be computed. This work extends previous work on privacy-preserving ontology publishing, in which a very restricted form of ABoxes, called instance stores, had been considered, but restricts the attention to compliance. The approach developed here can easily be adapted to the problem of computing optimal repairs of quantified ABoxes.
Baader, F., Kriegel, F., Nuradiansyah, A., PENALOZA NYSSEN, R. (2020). Computing Compliant Anonymisations of Quantified ABoxes w.r.t. EL Policies. In Proceedings of the 19th International Semantic Web Conference (ISWC 2020), Part I (pp.3-20). Springer Science and Business Media Deutschland GmbH [10.1007/978-3-030-62419-4_1].
Computing Compliant Anonymisations of Quantified ABoxes w.r.t. EL Policies
Rafael Penaloza
2020
Abstract
We adapt existing approaches for privacy-preserving publishing of linked data to a setting where the data are given as Description Logic (DL) ABoxes with possibly anonymised (formally: existentially quantified) individuals and the privacy policies are expressed using sets of concepts of the DL. We provide a chacterization of compliance of such ABoxes w.r.t. policies, and show how optimal compliant anonymisations of ABoxes that are non-compliant can be computed. This work extends previous work on privacy-preserving ontology publishing, in which a very restricted form of ABoxes, called instance stores, had been considered, but restricts the attention to compliance. The approach developed here can easily be adapted to the problem of computing optimal repairs of quantified ABoxes.File | Dimensione | Formato | |
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