WP. 44 ENGLISH ONLY UNITED NATIONS STATISTICAL COMMISSION and ECONOMIC COMMISSION FOR EUROPE CONFERENCE OF EUROPEAN STATISTICIANS EUROPEAN COMMISSION STATISTICAL OFFICE OF THE EUROPEAN COMMUNITIES (EUROSTAT)
نویسندگان
چکیده
The importance of being able to classify records according to disclosure risk is well understood; Skinner and Holmes (1998), Fienberg and Makov (1998). One concept for so classifying records is called special uniqueness; see Elliot (2000), Elliot et al (2002), Manning and Haglin (2005). This paper describes SUDA (Special Uniques Detection Algorithm) which is both a set of computer science algorithms and indeed a fully functioning software system for detecting and grading special uniques. Section 1 describes the basic design principles behind the sequential SUDA algorithm. Section 2 describes the software (now in use at the UK Office for National Statistics and Australian Bureau of Statistics). Section 3 describes recent advances (i) in parallelising SUDA and improving the algorithm so that cross-classifications of up to 60 variables can be comprehensively analysed (ii) in developing a version of SUDA for Grid computing.
منابع مشابه
WP.14 ENGLISH ONLY UNITED NATIONS STATISTICAL COMMISSION and ECONOMIC COMMISSION FOR EUROPE CONFERENCE OF EUROPEAN STATISTICIANS EUROPEAN COMMISSION STATISTICAL OFFICE OF THE EUROPEAN COMMUNITIES (EUROSTAT)
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WP. 9 ENGLISH ONLY UNITED NATIONS STATISTICAL COMMISSION and ECONOMIC COMMISSION FOR EUROPE CONFERENCE OF EUROPEAN STATISTICIANS EUROPEAN COMMISSION STATISTICAL OFFICE OF THE EUROPEAN COMMUNITIES (EUROSTAT)
The concept of differential privacy has received considerable attention in the literature recently. In this paper we evaluate the masking mechanism based on Laplace noise addition to satisfy differential privacy. The results of this study indicate that the Laplace based noise addition procedure does not satisfy the requirements of differential privacy.
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The European Union is facing the problem of releasing microdata in a multinational setting i.e. microdata stemming from twenty seven member states. Different laws, methodologies, practices and cultural approaches to confidentiality may severely limit the possibility of obtaining comprehensive anonymised data sets. We recall the approach adopted in Europe to design and manage harmonised statisti...
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WP. 30 ENGLISH ONLY UNITED NATIONS STATISTICAL COMMISSION and ECONOMIC COMMISSION FOR EUROPE CONFERENCE OF EUROPEAN STATISTICIANS EUROPEAN COMMISSION STATISTICAL OFFICE OF THE EUROPEAN COMMUNITIES (EUROSTAT)
We extend the safety rules used for the Statistical Disclosure Control of magnitude tables to include an intruder who models the ignorance about an unknown confidential quantity with a Uniform distribution. By applying this extension to the generalised p-rule we obtain the safety rules useful also in the presence of groups of respondents. The corresponding disclosure rules for different prior k...
متن کاملWP. 33 ENGLISH ONLY UNITED NATIONS STATISTICAL COMMISSION and ECONOMIC COMMISSION FOR EUROPE CONFERENCE OF EUROPEAN STATISTICIANS EUROPEAN COMMISSION STATISTICAL OFFICE OF THE EUROPEAN COMMUNITIES (EUROSTAT)
In order to manage the disclosure risk in frequency tables containing population counts, the tables undergo statistical disclosure control (SDC) methods. This results in information loss. We examine quantitative information loss measures for frequency tables and compare them across different SDC methods. We show examples of the information loss measures on real UK 2001 Census tables after they ...
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