Per citar aquest document: http://ddd.uab.cat/record/97850
Multiplicative noise for masking numerical microdata with constraints
Oganian, Anna (Georgia Southern University)

Data: 2011
Resum: Before releasing databases which contain sensitive information about individuals, statistical agencies have to apply Statistical Disclosure Limitation (SDL) methods to such data. The goal of these methods is to minimize the risk of disclosure of the confidential information and at the same time provide legitimate data users with accurate information about the population of interest. SDL methods applicable to the microdata (i. e. collection of individual records) are often called masking methods. In this paper, several multiplicative noise masking schemes are presented. These schemes are designed to preserve positivity and inequality constraints in the data together with the vector of means and covariance matrix.
Drets: Tots els drets reservats
Llengua: Anglès
Document: article ; recerca ; publishedVersion
Matèria: Statistical disclosure limitation (SDL) ; SDL method ; Multiplicative noise ; Positivity and inequality constraints
Publicat a: SORT : statistics and operations research transactions, Vol. Special, Núm. (2011) , p. 99-112, ISSN 1696-2281



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