• 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