A rejoinder to the comments by Polettini and Stander
Statistics and Computing
Journal of Computational Methods in Sciences and Engineering - Computational and Mathematical Methods for Science and Engineering Conference 2002 - CMMSE-2002
Privacy-Preserving Data Publishing
Foundations and Trends in Databases
Beyond k-Anonymity: A Decision Theoretic Framework for Assessing Privacy Risk
Transactions on Data Privacy
Efficient discovery of de-identification policy options through a risk-utility frontier
Proceedings of the third ACM conference on Data and application security and privacy
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In this paper we show how a simple model that captures user uncertainty can be used to define suitable measures of disclosure risk and data utility. The model generalizes previous results of Duncan and Lambert. We present several examples to illustrate how the new measures can be used to implement existing optimality criteria for the choice of the best form of data release.