statistical disclosure control method
Novel iterative min-max clustering to minimize information loss in statistical disclosure control
... clustering method of Ward et ...microaggregation method based on the fuzzy c-means algorithm [1], and Laszlo and Mukherjee [13] extended the standard minimum spanning tree partitioning algorithm for ...
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Multiple imputation: an alternative to top coding for statistical disclosure control
... MI has been proposed as a method of SDC (Little, 1993; Rubin, 1993; Little et al., 2004; Reiter, 2003, 2005a, b). An imputation model is built from the original data and observed val- ues are replaced by draws ...
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K−means clustering microaggregation for statistical disclosure control
... The reminder of this paper is organized as follows. We introduce a problem of microaggregation in Section 2. Section 3 introduces the basic concept of microag- gregation. We present a brief description of our proposed ...
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Systematic clustering-based microaggregation for statistical disclosure control
... microaggregation method, later called Maximum Distance (MD) method ...MD method repeatedly locates the two records that are most distant to each other, and forms two clusters with their respective (k ...
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Preserving edits when perturbing microdata for statistical disclosure control
... perturbative method called PRAM (the Post-Randomization Method) is sometimes used for masking ...This method adds “noise” to categorical variables by changing values of categories for a small number ...
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Studies on Protecting Privacy of Anonymized Medical Data
... Statistical Disclosure Control(SDC) family of method for micro data masking the micro data so that they can be released while preserving the ...
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Statistical disclosure control methods for census frequency tables
... their statistical analysis. This method however has yet to be implemented for a large scale ...practice, Statistical Agencies prefer record swapping since the method is easy to implement and ...
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Microaggregation sorting framework for k-anonymity statistical disclosure control in cloud computing
... microaggregation method is measured by calculating its information ...microaggregation method should incur as little information loss as ...clustering method of Ward et ...microaggregation ...
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New multi-dimensional sorting based k-anonymity microaggregation for statistical disclosure control
... microaggregation method must min- imize the information loss resulting from this replacement ...for Statistical Disclosure Control ...microaggregation method is used to create ...
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Pre processing optimisation applied to the classical integer programming model for statistical disclosure control
... in statistical disclosure con- ...either statistical tables to be protected quicker or larger statistical tables to be ...Optimal Method used in protecting statistical ...
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Statistical Disclosure Control for Data Privacy Preservation
... a Statistical Disclosure Control (SDC) method which is perturbative in ...popular method for micrdata protection which naturally satisfies k- Anonymity without generalization or ...data ...
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Semantic microaggregation for the anonymization of query logs using the open directory project
... Web search engines gather information from the queries performed by the user in the form of query logs. These logs are extremely useful for research, marketing, or profiling, but at the same time they are a great threat ...
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A genetic approach to statistical disclosure control
... perturbation method which maintains both additivity and the margin totals and has been shown to protect three- dimensional tables with up to 1,000,000 ...non-perturbation method is known as cell suppression ...
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Statistical Disclosure Control using Post Randomisation: Variants and Measures for Disclosure Risk
... for disclosure risk introduced in Skinner and Elliot (2002) can be extended to the situation where PRAM is applied before data are released by the statistical ...a disclosure control ...
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A Data Driven Statistical Approach for Monitoring and Analysis of Large Industrial Processes
... multi-model method, local model approach, and Bayesian inference method are suitable machine learning ...studied. Statistical monitoring methods heavily rely on the data collected from the field ...
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Disclosure control of analytical outputs
... outputs. Disclosure control methodologists have suggested variations on rules designed for tables (for example, minimum frequencies, no influential or dominant ...
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A simulation of selected statistical process control methods :a thesis presented in partial fulfilment of the requirements for the degree of Master of Technology at Massey University
... Many authors have described 'statistical process control' as the method used to determine the performance and to process if.. naturally and to effectively detect the.[r] ...
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Corporate Boards and Ownership Structure as Antecedents of Corporate Governance Disclosure in Saudi Arabian Publicly Listed Corporations
... Furthermore, the positive coefficients on BSZ, AFZ and CGC indicate that H4, H5, and H6, respectively, are supported. The positive relationship between BSZ and SCGI is in line with the evidence of previous studies ...
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Image Denoising using Statistical and Non Statistical Method
... the statistical nature of electromagnetic waves such as x-rays, visible lights and gamma ...by statistical quantum fluctuations, that is, variation in the number of photons sensed at a given exposure level ...
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Disclosure detection in research environments in practice
... to statistical disclosure detection and control (SDDC) struggle to accommodate the infinite variety of outputs produced in research ...designing statistical disclosure control ...
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