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DETERMINING JOURNALIST RISK OF A DATASET USING POPULATION EQUIVALENCE CLASS DISTRIBUTION ESTIMATION

机译:用总体等价类分布估计确定数据集的风险

摘要

Methods and systems to de-identify a longitudinal dataset of personal records based on journalistic risk computed from a sample set of the personal records, including determining a similarity distribution of the sample set based on quasi-identifiers of the respective personal records, converting the similarity distribution of the sample set to an equivalence class distribution, and computing journalistic risk based on the equivalence distribution. In an embodiment, multiple similarity measures are determined for a personal record based on comparisons with multiple combinations of other personal records of the sample set, and an average of the multiple similarity measures is rounded. In an embodiment, similarity measures are determined for a subset of the sample set and, for each similarity measure, the number of records having the similarity measure is projected to the subset of personal records. Journalistic risk may be computed for multiple types of attacks.
机译:用于基于从个人记录的样本集计算的新闻风险去识别个人记录的纵向数据集的方法和系统,包括基于各自个人记录的准标识符确定样本集的相似性分布,将样本集的相似性分布转换为等价类分布,基于等价分布计算新闻风险。在一个实施例中,基于与样本集的其他个人记录的多个组合的比较来确定个人记录的多个相似性度量,并且对多个相似性度量的平均值进行四舍五入。在一个实施例中,为样本集的子集确定相似性度量,并且对于每个相似性度量,具有相似性度量的记录的数量被投影到个人记录的子集。可以计算多种类型攻击的新闻风险。

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