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Data privacy employing a k-anonymity model with probabalistic match self-scoring
Data privacy employing a k-anonymity model with probabalistic match self-scoring
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机译:使用具有概率匹配自评分功能的k匿名模型进行数据隐私
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摘要
According to one embodiment of the present invention, a system for protecting data determines a desired duplication rate based on a level of desired anonymity for the data and generates a threshold for data records within the data based on the desired duplication rate. The system produces a data record score for each data record based on comparisons of attributes for that data record, compares the data record scores to the threshold, and controls access to the data records based on the comparison. Embodiments of the present invention further include a method and computer program product for protecting data in substantially the same manners described above.
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