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A mathematical framework to implement statistical databases

A mathematical framework to implement statistical databases The objective of this paper is to define a mathematical framework for statistical Databases (SDB) and to show how it can be implemented. Matrix algebra is used as a tool in the representation of statistical databases. The matrix algebra operations are considered the building blocks for the implementation of inference control methods. The rigor of this approach can be very beneficial for further studies on this topic. The implementation of Inference Control Methods for SDBs can be greatly simplified if this approach is used. Inference Control methods release aggregate information from a SDB about large subsets of records in a form that attempts to protect individual privacy. The implementation of specific Inference Control Methods (ICM) will be presented in a future publication. Several examples of typical operations on SDBs are presented in the text. SAS/IML was used to implement the ideas proposed here. The samples were prepared and tested using a personal computer (486 IBM/PC compatible) and a mainframe (IBM 4381) available at CSU, Chico. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png ACM SIGSAC Review Association for Computing Machinery

A mathematical framework to implement statistical databases

Costa, Miro
ACM SIGSAC Review , Volume 12 (2) – Apr 1, 1994
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References (10)

Publisher
Association for Computing Machinery
Copyright
Copyright © 1994 by ACM Inc.
ISSN
0277-920X
DOI
10.1145/182122.182124
Publisher site
See Article on Publisher Site

Abstract

The objective of this paper is to define a mathematical framework for statistical Databases (SDB) and to show how it can be implemented. Matrix algebra is used as a tool in the representation of statistical databases. The matrix algebra operations are considered the building blocks for the implementation of inference control methods. The rigor of this approach can be very beneficial for further studies on this topic. The implementation of Inference Control Methods for SDBs can be greatly simplified if this approach is used. Inference Control methods release aggregate information from a SDB about large subsets of records in a form that attempts to protect individual privacy. The implementation of specific Inference Control Methods (ICM) will be presented in a future publication. Several examples of typical operations on SDBs are presented in the text. SAS/IML was used to implement the ideas proposed here. The samples were prepared and tested using a personal computer (486 IBM/PC compatible) and a mainframe (IBM 4381) available at CSU, Chico.

Journal

ACM SIGSAC Review – Association for Computing Machinery

Published: Apr 1, 1994

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