Privacy-preserving data integration and sharing

Chris Clifton, Murat Kantarcioǧlu, An Hai Doan, Gunther Schadow, Jaideep Vaidya, Ahmed Elmagarmid, Dan Suciu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

117 Scopus citations

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.

Original languageEnglish (US)
Title of host publicationWorkshop Proceedings - The 9th Workshop on Research Issues in Data Mining and Knowledge Discovery, DMKD 2004, In Conjunction with ACM SIGMOD International Conference on Management of Data, SIGMOD-04
Pages19-26
Number of pages8
DOIs
StatePublished - 2004
Event9th Workshop on Research Issues in Data Mining and Knowledge Discovery, DMKD 2004, In Conjunction with ACM SIGMOD International Conference on Management of Data, SIGMOD-04 - Paris, France
Duration: Jun 13 2004Jun 13 2004

Publication series

NameProceedings of the ACM SIGMOD International Conference on Management of Data
ISSN (Print)0730-8078

Other

Other9th Workshop on Research Issues in Data Mining and Knowledge Discovery, DMKD 2004, In Conjunction with ACM SIGMOD International Conference on Management of Data, SIGMOD-04
Country/TerritoryFrance
CityParis
Period6/13/046/13/04

All Science Journal Classification (ASJC) codes

  • Software
  • Information Systems

Keywords

  • H.2.5 [DatabaseManagement]: Heterogeneous Databases
  • H.2.7 [Database Management]: Database Administration - Security, integrity, and protection
  • H.2.8 [Database Management]: Database Applications - Data mining
  • Security

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