基于加权关联规则挖掘的数据库风险识别仿真  

Database Risk Recognition Simulation Based on Weighted Association Rule Mining

作　　者：李娟[1] 张东圆 LI Juan;ZHANG Dong-yuan(Hebei Medical University Clinical college,Shijiazhaung Hebei 050000,China)

机构地区：[1]河北医科大学临床学院,河北石家庄050000

出　　处：《计算机仿真》2020年第12期366-370,共5页Computer Simulation

摘　　要：针对传统方法进行数据库风险识别时会出现查全率和查准率偏低这一问题,设计一种基于加权关联规则挖掘算法的数据库风险识别方法。利用加权关联规则挖掘算法的深度挖掘优势,提取数据库的风险特征,生成风险识别的加权系数,结合数据库的加权特征,确定风险识别权重值。从数据库的当机风险和补丁修复风险两方面,完成数据库风险的识别与标记。仿真结果表明,基于加权关联规则挖掘算法的数据库风险识别方法较传统方法的查全率高16.7%,查准率高21.6%。说明上述方法能够用于数据库的风险识别过程,且风险识别效果理想,具备更好地实际推广应用意义。Due to of low recall rate and precision rate in traditional database risk identification,this paper pro-posed a method of database risk identification based on weighted association rule mining algorithm.On the basis of advantages of weighted association rules mining algorithm on depth excavation,the risk features of database were ex-tracted.After that,the weighted coefficients of risk identification were generated.Combined with the weighted fea-tures of database,the weighted values of risk identification were determined.Thus,the identification and marking of database risk was finished from the system crash risk of database and the risk of patch repair.Simulation results show that the proposed method has 16.7%higher recall rate and 21.6%higher precision than the traditional method.Thus,the proposed method can be used in the risk identification of database.Meanwhile,the effect of risk identifica-tion is ideal,so the proposed method has better practical significance for popularization and application.

关 键 词：加权关联规则挖掘算法 数据库 风险识别 当机风险 补丁修复 

分 类 号：TM261[一般工业技术—材料科学与工程]