{"type":"ScholarlyArticle","title":"Revisiting Controlled Query Evaluation in Description Logics","authors":[{"name":"Domenico Lembo","slug":"domenico-lembo","given":"Domenico","family":"Lembo","affiliation":"Sapienza Università di Roma"},{"name":"Riccardo Rosati","slug":"riccardo-rosati","given":"Riccardo","family":"Rosati","affiliation":"Sapienza Università di Roma"},{"name":"Domenico Fabio Savo","slug":"domenico-fabio-savo","given":"Domenico Fabio","family":"Savo","affiliation":"Università degli Studi di Bergamo"}],"abstract":"Controlled Query Evaluation (CQE) is a confidentiality-preserving framework in which private information is protected through a policy, and a (optimal) censor guarantees that answers to queries are maximized without violating the policy. CQE has been recently studied in the context of ontologies, where the focus has been mainly on the problem of the existence of an optimal censor. In this paper we instead consider query answering over all possible optimal censors. We study data complexity of this problem for ontologies specified in the Description Logics DL-LiteR and EL_bottom and for variants of the censor language, which is the language used by the censor to enforce the policy. In our investigation we also analyze the relationship between CQE and the problem of Consistent Query Answering (CQA). Some of the complexity results we provide are indeed obtained through mutual reduction between CQE and CQA.","doi":"10.24963/ijcai.2019/247","url":"https://ijcai.org/proceedings/2019/247","pdf":"https://ijcai.org/proceedings/2019/0247.pdf","markdown":"https://ijcai.org/proceedings/2019/247.md","bibtex":"https://ijcai.org/proceedings/2019/bibtex/247","volume":{"slug":"2019","title":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2019","url":"https://ijcai.org/proceedings/2019/","year":2019,"location":"Macao","dates":"10-16 August 2019","editors":"Sarit Kraus","isbn":"978-0-9992411-4-1","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2019"},"section":"Knowledge Representation and Reasoning","track":"Main track","number":247,"pages":{"first":1786,"last":1792},"keywords":["Knowledge Representation and Reasoning: Computational Complexity of Reasoning","Knowledge Representation and Reasoning: Description Logics and Ontologies","Multidisciplinary Topics and Applications: Security and Privacy"],"videos":[],"references":[{"position":1,"raw":"[Baader et al., 2005] Franz Baader, Sebastian Brandt, and Carsten Lutz. 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