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

Record type: Article

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.

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Citation

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.

More information

Published date: 2008
Keywords: information loss, additive noise, micro-aggregation, post-randomization method, rank swapping, rounding

Identifiers

Local EPrints ID: 51967
URI: http://eprints.soton.ac.uk/id/eprint/51967
ISSN: 0282-423X
PURE UUID: 2b086ded-5e3d-441e-af4e-653e2fdf2931

Catalogue record

Date deposited: 07 Jul 2008
Last modified: 17 Jul 2017 14:47

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Contributors

Author: Natalie Shlomo
Author: Ton De Waal

University divisions


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