RiAiR: A Framework for Sensitive RDF Protection

Authors

  • M. Irvin Dongo Univ. Pau & Pays Adour, UPPA / E2S, LIUPPA, Anglet, France
  • Richard Chbeir Univ. Pau & Pays Adour, UPPA / E2S, LIUPPA, Anglet, France

Keywords:

RDF protection, Sensitive information, Semantic Web, Disclosure source

Abstract

The Semantic Web and the Linked Open Data (LOD) initiatives pro-mote the integration and combination of RDF data on the Web. In some cases, data need to be analyzed and protected before publication in order to avoid the disclosure of sensitive information. However, existing RDF techniques do not ensure that sensitive information cannot be discovered since all RDF resources are linked in the Semantic Web and the combination of different datasets could produce or disclose unexpected sensitive information. In this context, we propose a framework, called RiAiR, which reduces the complexity of the RDF structure in order to decrease the interaction of the expert user for the classification of RDF data into identifiers, quasi-identifiers, etc. An intersection process suggests disclosure sources that can compromise the data. Moreover, by a generalization method, we decrease the connections among resources to comply with the main objectives of integration and combination of the Semantic Web. Results show a viability and high performance for a scenario where heterogeneous and linked datasets are present.

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Author Biographies

M. Irvin Dongo, Univ. Pau & Pays Adour, UPPA / E2S, LIUPPA, Anglet, France

M. Irvin Dongo received his B.Sc. degree in Computer Science from the Catholic San Pablo University, Perú; and his M.Sc. and Ph.D. degrees from the University of Pau, France. He is currently under a postdoctoral position in Computer Science at École Supérieure des Technologies Industrielles Avancées (ESTIA). His research interests lie in normalization and anonymization of Web resources, knowledge-bases modeling (Semantic Web); policies and management of credentials, security model and anonymization technique; and machine/deep learning techniques for an analysis and classification of data to discover patters and gesture recognition.

Richard Chbeir, Univ. Pau & Pays Adour, UPPA / E2S, LIUPPA, Anglet, France

Richard Chbeir received his PhD in Computer Science from the University of INSA DE LYON-FRANCE in 2001 and then his Habilitation degree in 2010 from the University of Bourgogne. He is currently a Full Professor in the Computer Science Department in IUT de Bayonne in Anglet France. His current research interests are in the areas of multimedia information retrieval, XML and RSS Similarity, access control models, and digital ecosystems. Richard Chbeir has published in international journals, books, and conferences, and has served on the program committees of several international conferences. He is currently the Chair of the French Chapter ACM SIGAPP. Richard Chbeir teaches several courses in the Computer Science Department of the University of Pau University in Anglet-France.

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