Controlled Query Evaluation over Prioritized Ontologies with Expressive Data Protection Policies

2021 ◽  
pp. 374-391
Author(s):  
Gianluca Cima ◽  
Domenico Lembo ◽  
Lorenzo Marconi ◽  
Riccardo Rosati ◽  
Domenico Fabio Savo
Author(s):  
Bernardo Cuenca Grau ◽  
Evgeny Kharlamov ◽  
Egor V. Kostylev ◽  
Dmitriy Zheleznyakov

Author(s):  
Domenico Lembo ◽  
Riccardo Rosati ◽  
Domenico Fabio Savo

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.


Author(s):  
Gianluca Cima ◽  
Domenico Lembo ◽  
Riccardo Rosati ◽  
Domenico Fabio Savo

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.


Author(s):  
Gianluca Cima ◽  
Domenico Lembo ◽  
Lorenzo Marconi ◽  
Riccardo Rosati ◽  
Domenico Fabio Savo

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