A probabilistic approach for disclosure risk assessment in statistical databases

A probabilistic approach for disclosure risk assessment in statistical databases In this paper, disclosure risk assessment in Statistical Databases is performed by means of a probabilistic approach; in particular, we consider the problem of auditing databases that support statistical sum/count/mean/max/min queries to protect the privacy of sensitive boolean data. We provide both a theoretical framework for evaluating the disclosure risk and a tool for its control and management. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Quality & Quantity Springer Journals

A probabilistic approach for disclosure risk assessment in statistical databases

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Publisher
Springer Netherlands
Copyright
Copyright © 2015 by Springer Science+Business Media Dordrecht
Subject
Social Sciences; Methodology of the Social Sciences; Social Sciences, general
ISSN
0033-5177
eISSN
1573-7845
D.O.I.
10.1007/s11135-015-0173-5
Publisher site
See Article on Publisher Site

Abstract

In this paper, disclosure risk assessment in Statistical Databases is performed by means of a probabilistic approach; in particular, we consider the problem of auditing databases that support statistical sum/count/mean/max/min queries to protect the privacy of sensitive boolean data. We provide both a theoretical framework for evaluating the disclosure risk and a tool for its control and management.

Journal

Quality & QuantitySpringer Journals

Published: Feb 12, 2015

References

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