Research on dynamic and secure storage of financial data based on cloud platform

被引：0
|
作者：
Li, Jingyi [1 ]
机构：
[1] Jiaozuo Univ, Sch Accounting, Jiaozuo 454000, Henan, Peoples R China
来源：
WEB INTELLIGENCE | 2021年 / 19卷 / 04期
关键词：
Cloud platform; secure storage; CSA cloud risk model; rough set; granularity theory;
D O I：
10.3233/WEB-210472
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Traditional financial data storage methods are prone to data leakage and narrow data coverage. Therefore, this paper proposes a dynamic and secure storage method of financial data based on cloud platform.In order to improve the ability of enterprise data management, the paper constructs a financial cloud computing platform, mining financial data by rough set theory, and analyzing the results of frequent pattern mining of financial data by fuzzy attribute characteristics.According to the granularity theory, the financial data is classified and processed, and the CSA cloud risk model is established to realize the dynamic and secure storage of financial data.The experimental results show that. The maximum data storage delay of this method is no more than 4.1 s, the maximum data leakage risk coefficient is no more than 0.5, the number of data types can reach 30, and the data storage coverage is improved.
引用
收藏
页码：263 / 274
页数：12
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