Estimating the re-identification risk per record in microdata
Estimating the re-identification risk per record in microdata
A measure of re-identification risk at the record level has a variety of potential uses in statistical disclosure control for microdata. The conceptual basis of such a measure is considered. The risk is conceived of broadly as the evidence in support of a link between the record and the unit in the population from which it is derived. For discrete key variables subject to no measurement error, a measure is derived which reflects the probability that the record is unique in the population. Under certain assumptions, two approaches are described for estimating this measure from the microdata. These approaches are applied to a 10% sample of microdata from the 1991 Census in Great Britain. It is found that the resulting risk measures can indeed be used successfully to establish whether sample unique records are unique in the population. The implications of these findings are discussed.
key variable, log-linear model, lognormal distribution, population uniqueness, statistical disclosure control
361-372
Skinner, C.J.
48081d82-c596-436e-8846-c9d0a1bf158d
Holmes, D.J.
acb9dc00-6021-4eee-8219-2c5032d62ce7
1998
Skinner, C.J.
48081d82-c596-436e-8846-c9d0a1bf158d
Holmes, D.J.
acb9dc00-6021-4eee-8219-2c5032d62ce7
Skinner, C.J. and Holmes, D.J.
(1998)
Estimating the re-identification risk per record in microdata.
Journal of Official Statistics, 14 (4), .
Abstract
A measure of re-identification risk at the record level has a variety of potential uses in statistical disclosure control for microdata. The conceptual basis of such a measure is considered. The risk is conceived of broadly as the evidence in support of a link between the record and the unit in the population from which it is derived. For discrete key variables subject to no measurement error, a measure is derived which reflects the probability that the record is unique in the population. Under certain assumptions, two approaches are described for estimating this measure from the microdata. These approaches are applied to a 10% sample of microdata from the 1991 Census in Great Britain. It is found that the resulting risk measures can indeed be used successfully to establish whether sample unique records are unique in the population. The implications of these findings are discussed.
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Published date: 1998
Keywords:
key variable, log-linear model, lognormal distribution, population uniqueness, statistical disclosure control
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Local EPrints ID: 34237
URI: http://eprints.soton.ac.uk/id/eprint/34237
ISSN: 0282-423X
PURE UUID: d279b640-dcf4-48b6-8b5f-72e408854ecf
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Date deposited: 20 Dec 2007
Last modified: 11 Dec 2021 15:23
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Contributors
Author:
C.J. Skinner
Author:
D.J. Holmes
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