Record level measures of disclosure risk for survey microdata

Measures of disclosure risk at the record level have a variety of potential uses in statistical disclosure control for microdata. We propose a new record level measure of disclosure risk which is the probability that a unique match between a microdata record and a population unit is correct. For discrete key variables subject to no measurement error, we study this measure under the assumption of a Poisson model and a Poisson-gamma model. Moreover, we apply the approaches to a sample of microdata from the U.K. General Household Survey. The results indicate that the risk measure may be used to establish whether sample unique records are unique in the population.

[1]  A. Agresti.  An introduction to categorical data analysis , 1997 .

[2]  Chris J. Skinner,et al.  Estimation of a measure of disclosure risk for survey microdata under unequal probability sampling , 2003 .

[3]  Michael Carlson,et al.  Assessing Microdata Disclosure Risk Using the Poisson-Inverse Guassian Distribution , 2002 .

[4]  L. Willenborg,et al.  Statistical Disclosure Control and Sampling Weights , 1997 .

[5]  Pravin K. Trivedi,et al.  Regression Analysis of Count Data , 1998 .

[6]  A. Dale,et al.  Proposals for 2001 samples of anonymized records: An assessment of disclosure risk , 2001 .

[7]  Chris J. Skinner,et al.  Estimating the re-identification risk per record in microdata , 1998 .

[8]  D. Lambert,et al.  The Risk of Disclosure for Microdata , 1989 .

[9]  P. Doyle,et al.  Confidentiality, Disclosure and Data Access: Theory and Practical Applications for Statistical Agencies , 2001 .

[10]  S. Fienberg,et al.  Con ® dentiality , Uniqueness , and Disclosure Limitation for Categorical Data 1 , 1999 .

[11]  C. Skinner,et al.  A measure of disclosure risk for microdata , 2002 .

[12]  G. Paass.  Disclosure Risk and Disclosure Avoidance for Microdata , 1988 .

[13]  Luisa Franconi,et al.  Individual Risk Estimation in µ-Argus: A Review , 2004, Privacy in Statistical Databases.

[14]  S. M. Samuels.  A Bayesian , Species-Sampling-Inspired Approach to the Uniques Problem in Microdata Disclosure Risk Assessment , 1999 .

[15]  Ton de Waal,et al.  Statistical Disclosure Control in Practice , 1996 .

[16]  A. Bowman,et al.  Applied smoothing techniques for data analysis : the kernel approach with S-plus illustrations , 1999 .

[17]  L. Willenborg,et al.  Elements of Statistical Disclosure Control , 2000 .

[18]  Mark Elliot,et al.  Disclosure Risk Assessment , 2002 .

[19]  W. Keller,et al.  Disclosure control of microdata , 1990 .

[20]  D. Lambert.  Measures of Disclosure Risks and Harm , 1993 .

[21]  W. Cleveland.  Robust Locally Weighted Regression and Smoothing Scatterplots , 1979 .

[22]  J. N. K. Rao,et al.  Analysis of Categorical Response Data from Complex Surveys: An Appraisal and Update , 2003 .