Title :
Privacy-Preserving Reasoning on the SemanticWeb
Author :
Bao, Jie ; Slutzki, Giora ; Honavar, Vasant
Author_Institution :
Iowa State Univ., Ames
Abstract :
Many semantic web applications require selective sharing of ontologies between autonomous entities due to copyright, privacy or security concerns. In such cases, an agent might want to hide a part of its ontology while sharing the rest. However, prohibiting any use of the hidden part of the ontology in answering queries from other agents may be overly restrictive. We provide a framework for privacy- preserving reasoning in which an agent can safely answer queries against its knowledge base using inferences based on both the hidden and visible part of the knowledge base, without revealing the hidden knowledge. We show an application of this framework in the widely used special case of hierarchical ontologies.
Keywords :
data privacy; inference mechanisms; information retrieval; knowledge based systems; ontologies (artificial intelligence); semantic Web; hierarchical ontologies; inference mechanism; knowledge base; privacy-preserving reasoning; query answering; semantic Web; Biomedical imaging; Breast cancer; Calendars; Companies; Insurance; Ontologies; Privacy; Protection; Semantic Web; Sun;
Conference_Titel :
Web Intelligence, IEEE/WIC/ACM International Conference on
Conference_Location :
Fremont, CA
Print_ISBN :
978-0-7695-3026-0