We study information disclosure in Description Logic ontologies, in the spirit of Controlled Query Evaluation, where query answering is filtered through optimal censors maximizing answers while hiding data protected by a declarative policy. Previous works have considered limited forms of policy, typically constituted by conjunctive queries (CQs), whose answer must never be inferred by a user. Also, existing implementations adopt approximated notions of censors that might result too restrictive in the practice in terms of the amount of non-protected information returned to the users. In this paper we enrich the framework, by extending CQs in the policy with comparison predicates and introducing preferences between ontology predicates, which can be exploited to decide the portion of a secret that can be disclosed to a user, thus in principle augmenting the throughput of query answers. We show that answering CQs in our framework is first-order rewritable for DL- LiteA ontologies and safe policies, and thus in AC0 in data complexity. We also present some experiments on a popular benchmark, showing effectiveness and feasibility of our approach in a real-world scenario.

(2021). Controlled Query Evaluation over Prioritized Ontologies with Expressive Data Protection Policies . Retrieved from http://hdl.handle.net/10446/201340

Controlled Query Evaluation over Prioritized Ontologies with Expressive Data Protection Policies

Savo, Domenico Fabio
2021-01-01

Abstract

We study information disclosure in Description Logic ontologies, in the spirit of Controlled Query Evaluation, where query answering is filtered through optimal censors maximizing answers while hiding data protected by a declarative policy. Previous works have considered limited forms of policy, typically constituted by conjunctive queries (CQs), whose answer must never be inferred by a user. Also, existing implementations adopt approximated notions of censors that might result too restrictive in the practice in terms of the amount of non-protected information returned to the users. In this paper we enrich the framework, by extending CQs in the policy with comparison predicates and introducing preferences between ontology predicates, which can be exploited to decide the portion of a secret that can be disclosed to a user, thus in principle augmenting the throughput of query answers. We show that answering CQs in our framework is first-order rewritable for DL- LiteA ontologies and safe policies, and thus in AC0 in data complexity. We also present some experiments on a popular benchmark, showing effectiveness and feasibility of our approach in a real-world scenario.
2021
Cima, Gianluca; Lembo, Domenico; Marconi, Lorenzo; Rosati, Riccardo; Savo, Domenico Fabio
File allegato/i alla scheda:
File Dimensione del file Formato  
iswc.pdf

Solo gestori di archivio

Versione: publisher's version - versione editoriale
Licenza: Licenza default Aisberg
Dimensione del file 387.39 kB
Formato Adobe PDF
387.39 kB Adobe PDF   Visualizza/Apri
Pubblicazioni consigliate

Aisberg ©2008 Servizi bibliotecari, Università degli studi di Bergamo | Terms of use/Condizioni di utilizzo

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10446/201340
Citazioni
  • Scopus 2
  • ???jsp.display-item.citation.isi??? 1
social impact