Abstract
Both the (n,k)-dominance rule as well as the p%-rule are well known and often used sensitivity measures in determining which cells are unsafe to publish in tabular output. The p%-rule has some theoretical advantages over the dominance rule, hence it is generally advised to use that rule instead of the latter one.
In this paper we investigate the relation between the (n,k)-dominance rule and the p%-rule. We propose a dynamic rule to determine a value p *(k) that yields, approximately, the same number of unsafe cells as a corresponding (n,k)-dominance rule.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Cox, L.H.: Linear Sensitivity Measures in Statistical Disclosure Control. Journal of Statistical Planning and Inference 5, 153–164 (1981)
Cox, L.H.: Protecting Confidentiality in Establishment Surveys. In: Business Survey Methods, pp. 443–473. John Wiley & Sons, Chichester (1995)
Cox, L.H.: Disclosure Risk for Tabular Economic Data. In: Doyle, P., Lane, J., Theeuwes, J., Zayatz, L. (eds.) Confidentiality, Disclosure and Data Access: Theory and Practical Applications for Statistical Agencies ch. 8. Elsevier, New York (2001)
Domingo-Ferrer, J., Torra, V.: A critique of the sensitivity rules usually employed for statistical table protection. International Journal of Uncertainty Fuzziness and Knowledge-Based Systems 10, 545–556 (2002)
Hundepool, A., Domingo-Ferrer, J., Franconi, L., Giessing, S., Lenz, R., Naylor, J., Schulte Nordholt, E., Seri, G., de Wolf, P.P.: Handbook on Statistical Disclosure Control, version 1.2. ESSNet SDC deliverable (2010), http://neon.vb.cbs.nl/casc/SDC_Handbook.pdf
Hundepool, A., Domingo-Ferrer, J., Franconi, L., Giessing, S., Schulte Nordholt, E., Spicer, K., de Wolf, P.P.: Statistical Disclosure Control. Series in Survey Methodology. John Wiley & Sons, Chichester (2012)
Loeve, A.: Notes on sensitivity measures and protection levels. Research paper, Statistics Netherlands (2001), http://neon.vb.cbs.nl/casc/related/marges.pdf
Merola, G.: Safety Rules in Statistical Disclosure Control for Tabular Data. Working Paper of the Work Session on Statistical Data Confidentiality, Geneva, November 9-11 (2005), http://www.unece.org/fileadmin/DAM/stats/documents/ece/ces/ge.46/2005/wp.30.e.pdf
Robertson, D.A., Ethier, R.: Cell Suppression: Experience and Theory. In: Domingo-Ferrer, J. (ed.) Inference Control in Statistical Databases. LNCS, vol. 2316, pp. 8–20. Springer, Heidelberg (2002)
U.S. Federal Committee on Statistical Methodology. Statistical Policy Working Paper 22 (second version 2005), Report on Statistical Disclosure Limitation Methodology (2005), http://www.fcsm.gov/working-papers/SPWP22_rev.pdf
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
de Wolf, PP., Hundepool, A. (2012). p% Should Dominate. In: Domingo-Ferrer, J., Tinnirello, I. (eds) Privacy in Statistical Databases. PSD 2012. Lecture Notes in Computer Science, vol 7556. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33627-0_1
Download citation
DOI: https://doi.org/10.1007/978-3-642-33627-0_1
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33626-3
Online ISBN: 978-3-642-33627-0
eBook Packages: Computer ScienceComputer Science (R0)