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Privacy-preserving data publishing for horizontally partitioned databases

Published:26 October 2008Publication History

ABSTRACT

There is an increasing need for sharing data repositories containing personal information across multiple distributed, possibly untrusted, and private databases. Such data sharing is subject to constraints imposed by privacy of data subjects as well as data confidentiality of institutions or data providers. We developed a set of decentralized protocols that enable data sharing for horizontally partitioned databases given these constraints. Our approach includes a distributed anonymization protocol that allows independent data providers to build a virtual anonymized database, and a distributed querying protocol that allows clients to query the virtual database.

References

  1. P. Jurczyk and L. Xiong. Privacy-preserving data publishing for horizontally partitioned databases. Technical Report TR-2008-013, Emory University, Math&CS Dept., 2008.Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. K. LeFevre, D. DeWitt, and R. Ramakrishnan. Mondrian multidimensional k-anonymity. In IEEE ICDE, 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library

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  1. Privacy-preserving data publishing for horizontally partitioned databases

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    • Published in

      cover image ACM Conferences
      CIKM '08: Proceedings of the 17th ACM conference on Information and knowledge management
      October 2008
      1562 pages
      ISBN:9781595939913
      DOI:10.1145/1458082

      Copyright © 2008 ACM

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 26 October 2008

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