Abstract
The software SAFE has been developed at the State Statistical Institute Berlin-Brandenburg and has been in regular use there for several years now. It involves an algorithm that yields a controlled cell frequency perturbation. When a micro-data set has been protected by this method, any table which can be computed on the basis of this micro-data set will not contain any small cells, e.g. cells with frequency counts 1 or 2. We compare empirically observed transition probabilities resulting from this pre-tabular method to transition matrices in the context of variants of micro-data key based post-tabular random perturbation methods suggested in the literature, e.g. [8] and [4].
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References
Castro, J.: Minimum-distance controlled perturbation methods for large-scale tabular data protection. European Journal of Operational Research 171, 39–52 (2006)
Castro, J., González, J.A.: A Package for L1 Controlled Tabular Adjustment. Paper Presented at the Joint UNECE/Eurostat Work Session on Statistical Data Confidentiality, Bilbao (December 2-4, 2009), http://www.unece.org/stats/documents/2009.12.confidentiality.htm
Dandekar, R.H., Cox, L.: Synthetic Tabular Data – an Alternative to Complementary Cell Suppression (2002) (unpublished) (manuscript)
Fraser, B., Wooton, J.: A proposed method for confidentialising tabular output to protect against differencing. In: Monographs of Official Statistics. Work session on Statistical Data Confidentiality, Eurostat-Office for Official Publications of the European Communities, Luxembourg, pp. 299–302 (2006)
Höhne, J.: SAFE – ein Verfahren zur Geheimhaltung und Anonymisierung Statistischer Einzelangaben. In: Berliner Statistik - Statistische Monatsschrift 3/2003 (2003a)
Höhne, J.: SAFE - a method for statistical disclosure limitation of microdata. Paper Presented at the Joint ECE/Eurostat Worksession on Statistical Confidentiality in Luxembourg (2003b) (December 2007), http://www.unece.org/stats/documents/2003/04/confidentiality/wp.37.e.pdf
Leaver, V.: Implementing a method for automatically protecting user-defined Census tables. Paper Presented at the Joint ECE/Eurostat Worksession on Statistical Confidentiality in Bilbao (December 2009), http://www.unece.org/stats/documents/2009.12.confidentiality.htm
Shlomo, N., Young, C.: Invariant post-tabular protection of census frequency counts. In: Domingo-Ferrer, J., Saygın, Y. (eds.) PSD 2008. LNCS, vol. 5262, pp. 77–89. Springer, Heidelberg (2008)
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Giessing, S., Höhne, J. (2010). Eliminating Small Cells from Census Counts Tables: Some Considerations on Transition Probabilities. In: Domingo-Ferrer, J., Magkos, E. (eds) Privacy in Statistical Databases. PSD 2010. Lecture Notes in Computer Science, vol 6344. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15838-4_5
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DOI: https://doi.org/10.1007/978-3-642-15838-4_5
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