模糊微聚集为透明原理

Q1 Mathematics

Journal of Applied Logic Pub Date : 2017-09-01 DOI:10.1016/j.jal.2016.11.007

Vicenç Torra

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引用次数: 6

摘要

在隐私保护数据挖掘(PPDM)和统计披露控制(SDC)领域，微聚合已被证明是一种有效的数据保护方法。该方法包括对要保护的数据集应用聚类方法，然后用聚类代表替换每个数据。本文提出了一种基于模糊聚类的微聚集新方法。这种新方法的主要目标是在原始数据的聚类中心分配上不确定，同时在定义上简单。不确定性使我们能够克服标准微聚合所遭受的一些攻击。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Fuzzy microaggregation for the transparency principle

Microaggregation has been proven to be an effective method for data protection in the areas of Privacy Preserving Data Mining (PPDM) and Statistical Disclosure Control (SDC). This method consists of applying a clustering method to the data set to be protected, and then replacing each of the data by the cluster representative.

In this paper we propose a new method for microaggregation based on fuzzy clustering. This new approach has been defined with the main goal of being nondeterministic on the assignment of cluster centers to the original data, and at the same time being simple in its definition. Being nondeterministic permits us to overcome some of the attacks standard microaggregation suffers.

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