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Secure, Privacy-Preserving Analysis of Distributed Databases

Summary: [This abstract is based on the authors’ abstract.] When performing statistical analyses that require data from multiple distributed databases, barriers to integrating these data can be substantial. Secure multiparty computation and networking are information technology tools that can be used to perform statistically valid analyses of distributed databases in a manner that protects the confidentiality of each owner’s data. The focus in this study is horizontally partitioned data in which data records are spread among the databases. Protocols are presented for securely performing regression, maximum likelihood estimation, and Bayesian analysis. Three current research directions are outlined.

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  • Topics: Statistics
  • Keywords: Information technology, Statistical methods, Data processing, Data retrieval, Data analysis, Computation, Computer-based training (CBT),
  • Author: Karr, Alan F.; Fulp, William J.; Vera, Francisco; Young, S. Stanley; Lin, Xiaodong; Reiter, Jerome P.
  • Journal: Technometrics