Protection of micro-data subject to edit constraints against statistical disclosure

Shlomo, Natalie and De Waal, Ton (2008) Protection of micro-data subject to edit constraints against statistical disclosure Journal of Official Statistics, 24, (2), pp. 229-253.


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Before releasing statistical outputs, data suppliers have to assess if the privacy of statistical units is endangered and apply Statistical Disclosure Control (SDC) methods if necessary. SDC methods perturb, modify or summarize the data, depending on the format for releasing the data, whether as micro-data or tabular data. The goal is to choose an optimal method that manages disclosure risk while ensuring high-quality statistical data. In this article we discuss the effect of applying basic SDC methods on continuous and categorical variables for data masking. Perturbative SDC methods alter the data in some way. Changing values, however, will likely distort totals and other sufficient statistics and also cause fully edited records in micro-data to fail edit constraints, resulting in low-quality data. Moreover, an inconsistent record will signal that the record has been perturbed for disclosure control and attempts can be made to unmask the data. In order to deal with these problems, we develop new strategies for implementing basic perturbation methods that are often implemented at Statistical Agencies which minimize record level edit failures as well as overall measures of information loss.

Item Type: Article
ISSNs: 0282-423X (print)
Related URLs:
Keywords: information loss, additive noise, micro-aggregation, post-randomization method, rank swapping, rounding
ePrint ID: 51967
Date :
Date Event
Date Deposited: 07 Jul 2008
Last Modified: 16 Apr 2017 18:04
Further Information:Google Scholar

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