DocumentCode
2729105
Title
Privacy-Preserving Reasoning on the SemanticWeb
Author
Bao, Jie ; Slutzki, Giora ; Honavar, Vasant
Author_Institution
Iowa State Univ., Ames
fYear
2007
fDate
2-5 Nov. 2007
Firstpage
791
Lastpage
797
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Web Intelligence, IEEE/WIC/ACM International Conference on
Conference_Location
Fremont, CA
Print_ISBN
978-0-7695-3026-0
Type
conf
DOI
10.1109/WI.2007.83
Filename
4427191
Link To Document