重庆科技学院学报（自然科学版）2023，Vol.25Issue(6)：35-40,6.
非线性公共网络数据安全评测点挖掘方法研究
Research on Mining Methods for Data Security Evaluation Points in Nonlinear Public Networks
摘要
Abstract
The volume of nonlinear public network data is large,and there are complex and diverse nonlinear rela-tionships between the data.In order to improve the efficiency and accuracy of evaluation,a nonlinear public net-work data security evaluation point mining method is proposed.This paper builds a framework for mining nonlinear public network data security evaluation points,uses PTF sampling strategy to collect nonlinear public network data,conducts in-depth analysis and research on the factors affecting nonlinear public network data security,and pre-liminarily selects nonlinear public network data security evaluation points.The analytic hierarchy process is applied to calculate the weights of evaluation points and reasonable weight thresholds is given to obtain a preliminary mining set of nonlinear public network data security evaluation points.Partial least squares regression algorithm is applied to deeply mine the security evaluation points of nonlinear public network data.The experimental results show that this method has higher accuracy and more accurate mining results in mining nonlinear public network data security evaluation points.关键词
非线性公共网络/数据安全/评测点挖掘/网络数据管理Key words
nonlinear public network/data security/mining evaluation points/network data management分类
信息技术与安全科学引用本文复制引用
张宏武..非线性公共网络数据安全评测点挖掘方法研究[J].重庆科技学院学报（自然科学版）,2023,25(6):35-40,6.基金项目
2022 年宁夏高等学校重点科学研究项目"非线性公共网络数据安全评测点挖掘方法研究"(NYG2022072) （NYG2022072）
2023 年宁夏自然科学基金项目"强连通有向随机图的最小割问题在虚拟机部署中的应用研究"(2023AAC03357) （2023AAC03357）
