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Titlebook: Database Anonymization; Privacy Models, Data Josep Domingo-Ferrer,David Sánchez,Jordi Soria-Com Book 2016 Springer Nature Switzerland AG 20

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Beyond ,-Anonymity: ,-Diversity and ,-Closeness,hat an individual’s privacy must be protected if the corresponding record is hidden within a group of . records. However, this principle fails to provide sufficient protection when the records in the .-anonymous group have a similar value for the confidential attribute. In other words, .-anonymity p
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Differential Privacy by Individual Ranking Microaggregation,variate microaggregation to reduce the sensitivity (and, thus, the required amount of noise) in the masked records. Using multivariate microaggregation to reduce the sensitivity was complex because the change of a single record in a data set could lead to multiple changes in the microaggregation clu
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Conclusions and Research Directions,d/or attribute disclosure. These are tightly related to the two views of privacy that have been presented in Chapter 2: anonymity (it should not be possible to re-identify any individual in the published data) and confidentiality or secrecy (access to the released data should not reveal confidential
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Book 2016in detail connections between several privacy models (i.e., how to accumulate the privacy guaranteesthey offer to achieve more robust protection and when such guarantees are equivalent or complementary); we also explore the links between anonymization methods and privacy models (how anonymization me
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