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T-closeness is a traditional anonymization technique that is based on the logic of k-anonymity and goes beyond l-diversity to protect against attribute disclosure. The method requires more generalizations, namely that the distribution of the sensitive attribute in any equivalence class is close to the the distribution of the attribute in the overall table.