Privacy-preserving data integration and sharing

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. Categories and Subject Descriptors H.2.5 [Database Management]: Heterogeneous Databases; H.2.7 [Database Management]: Database Administration—Security, integrity, and protection; H.2.8 [Database Management]: Database Applications—Data mining General Terms Security

• Type: Conference
• Year: 2004
• Where: DMKD
• Authors: Chris Clifton, Murat Kantarcioglu, AnHai Doan, Gunther Schadow, Jaideep Vaidya, Ahmed K. Elmagarmid, Dan Suciu
• Keywords: Data Integration, Data Mining, Database Management, DMKD 2004