Abstract
Cell suppression for disclosure avoidance has a well-developed theory, unfortunately not sufficiently well known. This leads to confusion and faulty practices. Poor (sometimes seriously flawed) sensitivity rules can be used while inadequate protection mechanisms may release sensitive data. The negative effects on the published information are often exaggerated. An analysis of sensitivity rules will be done and some recommendations made. Some implications of the basic protection mechanism will be explained. A discussion of the information lost from a table with suppressions will be given, with consequences for the evaluation of patterns and of suppression heuristics. For most practitioners, the application of rules to detect sensitive economic data is well understood (although the rules may not be). However, the protection of that data may be an art rather than an application of sound concepts. More misconceptions and pitfalls arise.
The opinions expressed in this paper are those of the authors, and not necessarily those of Statistics Canada.
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References
Towards Automated Disclosure Analysis for Statistical Agencies. Gordon Sande; InternalDocument Statistics Canada (1977)
Automated Cell Suppression to Preserve Confidentiality of Business Statistics. Gordon Sande; Stat. Jour U.N. ECE2 pp33–41 (1984)
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Improving Statistics Canada’s Cell Suppression Software (CONFID). D. A. Robertson, COMPSTAT 2000 Proceedings in Computational Statistics. Ed. J.K Bethlehem, P.G.M van der Heiden, Physica Verlag (Heidelberg New York) (2000)
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© 2002 Springer-Verlag Berlin Heidelberg
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Robertson, D.A., Ethier, R. (2002). Cell Suppression: Experience and Theory. In: Domingo-Ferrer, J. (eds) Inference Control in Statistical Databases. Lecture Notes in Computer Science, vol 2316. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-47804-3_2
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DOI: https://doi.org/10.1007/3-540-47804-3_2
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