基于数据挖掘的电力无线通信网络漏洞检测

Vulnerability detection of power wireless communication network based on data mining

为了有效挖掘网络漏洞,防止电力无线通信被恶意攻击,提出了基于数据挖掘的电力无线通信网络漏洞检测方法。以定量分析方式确定模糊属性,结合电力无线通信网络动态环境,挖掘网络漏洞信息。对所有特征子集进行差极性分析,形成风险数据集,实现风险数据聚类。使用支持向量机训练数据集,根据黑盒遗传算法进行交叉测试,获取网络安全态势评估结果。构建网络数据挖掘漏洞模型,结合关联规则集进行网络漏洞检测。由实验结果可知,该方法漏洞数量检测结果与实际漏洞数量仅相差2个,具有精准的漏洞检测结果。

In order to effectively mine network vulnerabilities and prevent power wireless communication from being maliciously attacked,a vulnerability detection method of power wireless communication network based on data mining was proposed.Fuzzy attributes are determined by quantitative analysis,and network vulnerability information is mined based on the dynamic environment of power wireless communication network.All feature subsets are analyzed with differential polarity to form risk data sets and realize risk data clustering.The network security situation assessment results were obtained by crosstesting with support vector machine training data set and black box genetic algorithm.The vulnerability model of network data mining is constructed and the network vulnerability is detected by association rule set.According to the experimental results,the difference between the number of vulnerabilities detected by this method and the actual number of vulnerabilities is only 2,which has accurate vulnerability detection results.