Practical Data-Oriented Microaggregation for Statistical Disclosure Control
IEEE Transactions on Knowledge and Data Engineering
LHS-Based Hybrid Microdata vs Rank Swapping and Microaggregation for Numeric Microdata Protection
Inference Control in Statistical Databases, From Theory to Practice
Software—Practice & Experience - Focus on Selected PhD Literature Reviews in the Practical Aspects of Software Technology
Information fusion in data privacy: A survey
Information Fusion
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Previous work by these authors has been directed to measuring the performance of microdata masking methods in terms of information loss and disclosure risk. Based on the proposed metrics, we show here how to improve the performance of any particular masking method. In particular, post-masking optimization is discussed for preserving as much as possible the moments of first and second order (and thus multivariate statistics) without increasing the disclosure risk. The technique proposed can also be used for synthetic microdata generation and can be extended to preservation of all moments up to m-th order, for any m.