AAAI Publications, Thirty-First AAAI Conference on Artificial Intelligence

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Source Information Disclosure in Ontology-Based Data Integration
Michael Benedikt, Bernardo Cuenca Grau, Egor V. Kostylev

Last modified: 2017-02-12

Abstract


Ontology-based data integration systems allow users to effectively access data sitting in multiple sources by means of queries over a global schema described by an ontology. In practice, datasources often contain sensitive information that the data owners want to keep inaccessible to users. In this paper, we formalize and study the problem of determining whether a given data integration system discloses a source query to an attacker. We consider disclosure on a particular dataset, and also whether a schema admits a dataset on which disclosure occurs. We provide lower and upper bounds on disclosure analysis, in the process introducing a number of techniques for analyzing logical privacy issues in ontology-based data integration.

Keywords


logic; ontology; rule

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