Statistical Disclosure Control in Practice by Leon Willenborg, Ton de Waal

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By Leon Willenborg, Ton de Waal

The goal of this e-book is to debate a variety of points linked to disseminating own or company information accumulated in censuses or surveys or copied from administrative assets. the matter is to provide the knowledge in the sort of shape that they're invaluable for statistical study and to supply enough safeguard for the participants or companies to whom the information refer. the main a part of this publication is anxious with how to find the disclosure challenge and the way to accommodate it in useful circumstances.

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Apparently, the number of correctly matched records after application of the method by PaaB and Wauschkuhn was in disagreement with the probability of re-identification per record. It seems that the method of PaaB and Wauschkuhn does not provide us with the desired probability of re-identification per record. However, the method does have its strong points, such as the idea of considering different scenarios, the assumption of measurements errors in the microdata file and the identification file, and the use of discriminant analysis.

Primary suppression alone is generally not sufficient to obtain a table which is safe for release. In a table the marginal totals are mostly given as well as the values of the cells. The value of a cell which has been suppressed can then often be re-computed by means of the marginal totals. Therefore, additional cells have to be suppressed in order to eliminate this possibility. This is called secondary suppression. Secondary suppression can be done in many different ways. Usually secondary suppression aims to optimize some target function, expressing "information loss".

Only by finding a balance between either goal the problem may be solved. We shall not dwell upon this matter any further. A reader interested in a perturbation technique like data swapping is referred to [15] and [59]. Adding noise is discussed in [37] for instance. In SDC some of the users of the data should be looked upon as potential attackers. It is useful to consider the ways in which disclosure can take place. An attacker tries to match, consciously or subconsciously, records from the microdata set with records from an identification file or with individuals from his circle of acquaintances.

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