Privacy-preserving data mining demonstrator

Martin Beck, Michael Marhöfer
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引用次数: 13

Abstract

We present a system for demonstrating anonymized data mining on user profiles, which also evaluates the remaining utility of the generalized information through comparison of the classification results. The use case for this scenario builds around profiles containing personally identifiable information, which should be analyzed and classified by a third party. Our goal is to preserve the privacy of the users while maintaining a certain level of utility to allow data mining over the anonymized information.
保护隐私的数据挖掘演示
我们提出了一个系统,用于演示用户配置文件的匿名数据挖掘,该系统还通过比较分类结果来评估广义信息的剩余效用。此场景的用例围绕包含个人可识别信息的配置文件构建,这些信息应该由第三方进行分析和分类。我们的目标是保护用户的隐私,同时保持一定程度的实用程序,以允许对匿名信息进行数据挖掘。
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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