一种基于粗糙集的信息隐藏方法

Taorong Qiu, Zhi-yong Xiong, Xiaoming Bai, Shujie Xiong
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引用次数: 0

摘要

随着互联网的飞速发展,如何在敏感或重要信息的公开与隐私信息的匿名化之间寻求平衡显得尤为重要。本文提出了基于VPRS模型和粒度理论的β-重要性来有效地隐藏数据。当我们从信息表中获取重要属性时,再对不重要属性的值进行扩展处理。的用户,信息的粒度变得粗糙,所以我们实现匿名化。提出了相应的算法,并将该方法应用于一个实例,结果表明该方法是可行的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Approach to Information Hiding Based on Rough Set
With the rapid development of Internet, It is important to seek a balance between the publicity of sensitive or important information and the anonymisation of privacy information. In this paper, we propose β-Importance based on VPRS model and granularity theory to hide data effectively. When we obtain the important attributes from the information table, and then handle the values of unimportant attributes to extend. In term of users, the granularity of information become rough, so we achieve the anonymisation. We propose the relevant algorithm and apply this method to a real example, the results show that the proposed method is feasible.
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