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Probabilistic measure on aggregations (data security)

机译:概率衡量聚合(数据安全性)

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Proposes a probabilistic type of measure theory which estimates the amount of security relevant information of every subset of a given aggregate. This probabilistic measure theory provides each application a means or mechanism to furnish the system a numerical measure to assist the system security officer for making decisions on releasing or downgrading the internal data of the aggregate. A scenario for solving the aggregation problems during the design phase is proposed. In developing this work, two guiding principles are applied: Minimum Aggregation Principle (MAP) and the Maximum Protection Principle (MPP). MAP keeps both the number of elements in an aggregation and the number of aggregates to a minimum, while MPP keeps the unnecessary risks to a minimum.
机译:提出了一种概率类型的测量理论,其估计给定总计的每个子集的安全相关信息量。这种概率测量理论提供了每个应用程序的一种方法或机制来提供系统的数值措施,以帮助系统安全官员做出关于释放或降低总汇总的内部数据的决定。提出了一种用于解决设计阶段的聚集问题的场景。在开发这项工作时,应用了两个指导原则:最小聚合原理(地图)和最大保护原理(MPP)。 MAP将聚合中的元素数量和集合数量保持在最小值,而MPP将不必要的风险保持为最小值。

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