Secure analysis of distributed chemical databases without data integration.

Published

Journal Article

We present a method for performing statistically valid linear regressions on the union of distributed chemical databases that preserves confidentiality of those databases. The method employs secure multi-party computation to share local sufficient statistics necessary to compute least squares estimators of regression coefficients, error variances and other quantities of interest. We illustrate our method with an example containing four companies' rather different databases.

Full Text

Duke Authors

Cited Authors

  • Karr, AF; Feng, J; Lin, X; Sanil, AP; Young, SS; Reiter, JP

Published Date

  • September 2005

Published In

Volume / Issue

  • 19 / 9-10

Start / End Page

  • 739 - 747

PubMed ID

  • 16267693

Pubmed Central ID

  • 16267693

Electronic International Standard Serial Number (EISSN)

  • 1573-4951

International Standard Serial Number (ISSN)

  • 0920-654X

Digital Object Identifier (DOI)

  • 10.1007/s10822-005-9011-5

Language

  • eng