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Before releasing an anonymized data set, the data protector must know how safe the data set is, that is, how much disclosure risk is incurred by the release. If no privacy model is used to select specific privacy guarantees prior to anonymization, posterior disclosure risk assessment must be performed based on the anonymized data set and, if the result is not satisfactory, anonymization must be repeated...
k-Anonymity is a privacy property used to limit the risk of re-identification in a microdata set. A data set satisfying k-anonymity consists of groups of k records which are indistinguishable as far as their quasi-identifier attributes are concerned. Hence, the probability of re-identifying a record within a group is 1/k. We introduce the probabilistic k-anonymity property, which relaxes the indistinguishability...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.