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Hiding the Presence of Individuals from Shared Databases

机译:隐藏共享数据库中个人的存在

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Advances in information technology, and its use in research, are increasing both the need for anonymized data and the risks of poor anonymization. We present a metric, δ-presence, that clearly links the quality of anonymization to the risk posed by inadequate anonymization. We show that existing anonymization techniques are inappropriate for situations where δ-presence is a good metric (specifically, where knowing an individual is in the database poses a privacy risk), and present algorithms for effectively anonymizing to meet δ-presence. The algorithms are evaluated in the context of a real-world scenario, demonstrating practical applicability of the approach.
机译:信息技术的进步及其在研究中的应用,不仅增加了对匿名数据的需求,还增加了匿名性差的风险。我们提出了一个δ-presence度量,该度量将匿名化的质量与匿名化不充分所带来的风险明确地联系在一起。我们表明,现有的匿名化技术不适用于δ存在是一个很好的指标的情况(特别是知道数据库中的个人构成隐私风险的情况),并提出了有效进行匿名化以满足δ存在的算法。这些算法是在实际情况下进行评估的,证明了该方法的实际适用性。

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