摘要
针对云环境下数据安全和数据集敏感元素无法自动识别、自动动态分级的问题,提出一种面向文档级别的敏感元素自动化识别与动态分级算法,利用大数据语义识别技术,对各类文档的数据价值元素进行自动化提取,采用向量化处理的方式得到文档的特征向量,结合特征向量相似度量化文档的敏感度从而实现文档的自动分类分级。实验表明,该算法能够比较准确地识别并分类任意规模、非结构化的文档敏感元素,该算法无须提前知道文档敏感元素的特征,敏感特征字典,兼顾了平台存储安全的效率和安全性。
In order to solve the problems of the inability to automatically identify and dynamically classify the data security and sensitive elements of data sets in cloud environment,this paper presents a document-oriented algorithm for automatic identification and dynamic classification of sensitive elements.Specifically the big data semantic recognition technology is used to automatically extract the data value elements of various documents,and the feature vector of the document is obtained by vectorization methods,and the sensitivity of the document is quantified by combining the similarity of the feature vector to realize the automatic classification and grading of documents.Experimental results show that the algorithm can accurately identify and classify the sensitive elements of unstructured documents with any scale.The algorithm does not need to know the characteristics of sensitive elements and sensitive feature dictionary in advance,which balances the efficiency and security of platform storage security.
作者
胡志达
HU Zhida(Tiaryin Branch of China Telecom Co.,Ltd.,Tianjin 300385,China)
出处
《移动通信》
2020年第8期56-59,共4页
Mobile Communications
关键词
数据敏感性
语义识别
价值元素
存储安全
data sensitivity
semantic recognition
value element
storage security
