基于几何变形的大数据安全隐私保护方法

隐私保护已经成为大数据安全的重要研究内容之一。在分析了影响大数据安全隐私三个方面的基础上,提出了一种基于几何变形的大数据安全隐私保护方法。该方法从数据源的角度出发,使用几何变形的方法对数据进行干扰,使得数据聚类算法失效或分析得出错误的结果,从而达到大数据安全隐私保护的目的。在实际使用中,该方法效果良好。

Privacy Protection of Big Data Security based on Geometric Transformation

Privacy protection becomes an important research topic of big data security. This paper firstly analyzes the three factors of big data security, and then proposes a privacy protection method of big data security based on geometric transformation. This method, from the perspective of data source,and with geometric transformation technique,interferes with the data, thus to make the clustering algorithm lose efficacy or acquire inaccurate results,and further to achieve privacy protection of big data security.The practical application indicates that the proposed method is feasible and effective.