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Personalized information is removed from the original data to protect personal or private information is anonymization. The data anonymization can be performed in many ways, but in this paper the k-anonymization approach is used. If an owner owns a k-anonymous database and needs to determine whether the database, when inserted with a tuple owned by others, is still k-anonymous. The access to the database is strictly controlled, because for example data are used for certain experiments that need to be maintained confidential. Allowing the owner to directly read the contents of the tuple breaks the privacy of others (for example, salary information of individuals).
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