Abstract
A global measure of the re-identification risk in microdata files is analyzed. Two extensions of the log-linear models are presented. The first methodology considers the weights in the analysis of contingency tables. The results of several tests performed on real data are presented. In the framework of statistical disclosure control, the second methodology proposes a maximum penalized likelihood approach to the computation of smooth estimates.
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References
Agresti, A.: Categorical Data Analysis. Wiley, New York (1990)
Clogg, C.C., Eliason, S.R.: Some Common Problems in Log-Linear Analysis. Sociological Methods and Research 16, 8–44 (1987)
Elamir, E.A.H.: Analysis of Re-Identification Risk Based on Log-Linear Models. In: Domingo-Ferrer, J., Torra, V. (eds.) PSD 2004. LNCS, vol. 3050, pp. 273–281. Springer, Heidelberg (2004)
Fan, J., Gijbels, I.: Local Polynomial Modelling and its Applications. Chapman & Hall, London (1996)
Fienberg, S.E., Holland, P.W.: On the Choice of Flattening Constants for Estimating Multinomial Probabilities. Journal of Multivariate Analysis 2, 127–134 (1972)
Haberman, S.J.: Analysis of Qualitative Data. New Developments, vol. 2. Academic Press, New York (1979)
Lohr, S.L.: Sampling: Design and Analysis. Duxbury Press (1999)
Polettini, S.: Some Remarks on the Individual Risk Methodology. Monographs of Official Statistics. In: Work Session on Statistical Data Confidentiality. European Comission (2003)
Rao, J.N.K., Thomas, D.R.: The Analysis of Cross-Classified Categorical Data from Complex Surveys. Sociological Methodology 18, 213–269 (1988)
Rinott, Y., Shlomo, N.: A Smoothing Model for Sample Disclosure Risk Estimation. In: Tomography, Networks and Beyond. IMS Lecture Notes-Monograph Series Complex Datasets and Inverse Problems, vol. 54, pp. 161–171 (2007)
Skinner, C.J., Shlomo, N.: Assessing Identification Risk in Survey Micro-data Using Log Linear Models. Journal of American Statistical Association, Applications and Case Studies (forthcoming)
Simonoff, J.S.: A Penalty Function Approach to Smoothing Large Sparse Contingency Tables. The Annals of Statistics 11, 208–218 (1983)
Skinner, C., Holmes, D.: Estimating The Re-Identification Risk per Record in Microdata. J. Official Statistics 14, 361–372 (1998)
Willenborg, L., De Waal, T.: Elements of Disclosure Control. Lecture Notes in Statistics, vol. 155. Springer, Berlin (2001)
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Ichim, D. (2008). Extensions of the Re-identification Risk Measures Based on Log-Linear Models. In: Domingo-Ferrer, J., Saygın, Y. (eds) Privacy in Statistical Databases. PSD 2008. Lecture Notes in Computer Science, vol 5262. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87471-3_17
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DOI: https://doi.org/10.1007/978-3-540-87471-3_17
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-87470-6
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