Utility-Based Anonymization Using Generalization Boundaries to Protect Sensitive Attributes

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Privacy preserving data mining (PPDM) has become more and more important because it allows sharing of privacy sensitive data for analytical purposes. A big number of privacy techniques were developed most of which used the k-anonymity property which have
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