By Leon Willenborg, Ton de Waal
Statistical disclosure keep watch over is the self-discipline that offers with generating statistical information which are secure sufficient to be published to exterior researchers. This e-book concentrates at the method of the world. It offers with either microdata (individual info) and tabular (aggregated) facts. The ebook makes an attempt to strengthen the speculation from what will be referred to as the paradigm of statistical confidentiality: to switch dangerous facts in one of these method that secure (enough) info emerge, with minimal details loss. This booklet discusses what secure info, are, how details loss will be measured, and the way to change the knowledge in a (near) optimum method. as soon as it's been made up our minds tips on how to degree protection and knowledge loss, the creation of secure facts from detrimental info is usually a subject of fixing an optimization challenge. a number of such difficulties are mentioned within the ebook, and so much of them change into challenging difficulties that may be solved merely nearly. The authors current new effects that experience no longer been released prior to. The ebook isn't an outline of a space that's closed, yet, to the contrary, one who nonetheless has many spots looking ahead to to be extra totally explored. a few of these are indicated within the publication. The e-book may be important for reliable, social and clinical statisticians and others who're serious about freeing own or company info for statistical use. Operations researchers can be drawn to the optimization difficulties concerned, really for the demanding situations they current. Leon Willenborg has labored on the division of Statistical equipment at statistics Netherlands on account that 1983, first as a researcher and because 1989 as a senior researcher. considering that 1989 his major box of analysis and consultancy has been statistical disclosure regulate. From 1996-1998 he was once the venture coordinator of the european co-funded SDC project.
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Extra info for Elements of Statistical Disclosure Control
Microdata or tables, to protect them against disclosure attacks, lead to a loss of information content in the data. When a data protector protects a set of data interactively, he usually has in mind how to protect the data, i. e. formal measures for information loss are not used. He then is able to compare the various possibilities to get a safe data set. It is only in case that a computer program has to make such decisions that formal information loss measures are necessary. Such measures are then used as counterweights for the SDC actions.
28 1. Overview of the Area Suppression of variables is applied for instance to formal identifiers such as Name and Address. 5. Top and bottom coding. This is applied to ordinal variables. A top category is formed, covering the values of the variable above a specified upper threshold ()u. Similarly, a bottom category may be formed covering values below some other specified lower threshold () L. The problem in practice is to determine appropriate values for () Land ()u, given a particular approach to measuring disclosure risk.
In case of frequency tables we have that Yi = 1 for each i. We then should also take the weights Wi and take for granted that a cell total LiEC Wi is not an integer as LiEC 1. Evidently, the multipliers Wi should be kept secret by the data protector. 9 Disclosure Protection Techniques for Tables 37 We shall call this table protection technique Source Data Perturbation (SDP). The advantage of SDP-as a technique applied at the level of the source data-is that consistency between cell values in different tables derived from the same perturbed microdata set, is guaranteed.