Iliana M. Petrova

Piero A. Bonatti, Iliana M. Petrova, Luigi Sauro

DL^N is a recent approach that extends description logics with defeasible reasoning capabilities. In this paper we provide an overview on DL^N, illustrating the underlying knowledge engineering requirements as well as the characteristic features that preserve DL^N from some recurrent semantic and computational drawbacks. We also compare DL^N with some alternative nonmonotonic semantics, enlightening the relationships between the KLM postulates and DL^N.

Piero A. Bonatti, Sabrina Kirrane, Iliana M. Petrova et al.

The European General Data Protection Regulation (GDPR) calls for technical and organizational measures to support its implementation. Towards this end, the SPECIAL H2020 project aims to provide a set of tools that can be used by data controllers and processors to automatically check if personal data processing and sharing complies with the obligations set forth in the GDPR. The primary contributions of the project include: (i) a policy language that can be used to express consent, business policies, and regulatory obligations; and (ii) two different approaches to automated compliance checking that can be used to demonstrate that data processing performed by data controllers / processors complies with consent provided by data subjects, and business processes comply with regulatory obligations set forth in the GDPR.

P. A. Bonatti, L. Ioffredo, I. M. Petrova et al.

We address the problem of complying with the GDPR while processing and transferring personal data on the web. For this purpose we introduce an extensible profile of OWL2 for representing data protection policies. With this language, a company's data usage policy can be checked for compliance with data subjects' consent and with a formalized fragment of the GDPR by means of subsumption queries. The outer structure of the policies is restricted in order to make compliance checking highly scalable, as required when processing high-frequency data streams or large data volumes. However, the vocabularies for specifying policy properties can be chosen rather freely from expressive Horn fragments of OWL2. We exploit IBQ reasoning to integrate specialized reasoners for the policy language and the vocabulary's language. Our experiments show that this approach significantly improves performance.

P. A. Bonatti, L. Ioffredo, I. Petrova et al.

This paper shows how knowledge representation and reasoning techniques can be used to support organizations in complying with the GDPR, that is, the new European data protection regulation. This work is carried out in a European H2020 project called SPECIAL. Data usage policies, the consent of data subjects, and selected fragments of the GDPR are encoded in a fragment of OWL2 called PL (policy language); compliance checking and policy validation are reduced to subsumption checking and concept consistency checking. This work proposes a satisfactory tradeoff between the expressiveness requirements on PL posed by the GDPR, and the scalability requirements that arise from the use cases provided by SPECIAL's industrial partners. Real-time compliance checking is achieved by means of a specialized reasoner, called PLR, that leverages knowledge compilation and structural subsumption techniques. The performance of a prototype implementation of PLR is analyzed through systematic experiments, and compared with the performance of other important reasoners. Moreover, we show how PL and PLR can be extended to support richer ontologies, by means of import-by-query techniques. PL and its integration with OWL2's profiles constitute new tractable fragments of OWL2. We prove also some negative results, concerning the intractability of unrestricted reasoning in PL, and the limitations posed on ontology import.

Piero Andrea Bonatti, Iliana Mineva Petrova, Luigi Sauro

We introduce optimization techniques for reasoning in DLN---a recently introduced family of nonmonotonic description logics whose characterizing features appear well-suited to model the applicative examples naturally arising in biomedical domains and semantic web access control policies. Such optimizations are validated experimentally on large KBs with more than 30K axioms. Speedups exceed 1 order of magnitude. For the first time, response times compatible with real-time reasoning are obtained with nonmonotonic KBs of this size.