基于关联规则的网络漏洞信息数据挖掘方法

Data Mining Method of Network Vulnerability Information Based on Association Rules

为提高对网络漏洞信息数据的挖掘效率,提出关联规则下网络漏洞信息数据的挖掘方法。通过粒子群空间聚类算法生成关联规则,构建决策树挖掘漏洞,建立适应度函数来评价漏洞信息数据的挖掘效率,完成对网络漏洞信息数据的有效挖掘。实验结果表明,运用该方法挖掘网络漏洞信息数据时,构建决策树所消耗的时间较短,挖掘方法效率较高,能够有效处理大量的数据集。

To improve the efficiency of mining network vulnerability information data,a mining method for network vulnerability information data under association rules is proposed.The association rules are generated by the particle swarm spatial clustering algorithm,the decision tree is constructed to mine vulnerabilities,and the fitness function is established to evaluate the mining efficiency of vulnerability information data,so as to complete the effective mining of network vulnerability information data.The experimental results show that when using this method to mine network vulnerability information data,the time required to construct a decision tree is shorter,the mining method is more efficient,and can effectively process a large number of datasets.