Privacy-preserving data integration and sharing
Published 13 June 2004
Chris Clifton, Murat Kantarcıoğlu, AnHai Doan, Gunther Schadow, Jaideep Vaidya, Ahmed K. Elmagarmid
Citations188
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TL;DR
A privacy framework for data integration is laid out, in the context of existing accomplishments in data integration, that addresses challenges and opportunities for the data mining community.
Abstract
Integrating data from multiple sources has been a longstanding challenge in the database community. Techniques such as privacy-preserving data mining promises privacy, but assume data has integration has been accomplished. Data integration methods are seriously hampered by inability to share the data to be integrated. This paper lays out a privacy framework for data integration. Challenges for data integration in the context of this framework are discussed, in the context of existing accomplishments in data integration. Many of these challenges are opportunities for the data mining community.
Keywords
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