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dataPrivacy

Publishing data containing personal information about individuals is needed to export statistical conclusions. The publication of these data without revealing the true identity of individuals is an important problem. These data contain personal information, therefore the information should be hidden. It is possible, however, an attacker to be able to combine data from various published sources and his information to break the data anonymization. In this paper we present a tool for visualizing an existing implementation of algorithms for data anonymization. Specifically, with the implemented tool the user can regulate the process of anonymisation on a specific data set with respect to the following competitive criteria: (a) the degree of privacy achieved by the anonymisation algorithm, (b) the number of records deleted as outliers and (c) the degree of generalization of the data set.

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