基于模糊逻辑的无线网络安全态势预测系统

Wireless network security situation prediction system based on fuzzy logic

为了解决现有方法预测无线网络安全态势过程中存在的预测行为不及时、预测结果不精准的问题,提出了基于模糊逻辑的无线网络安全态势预测系统。利用日志类传感器获取相关参数,去除存在的大量冗余数据。利用Snort入侵检测系统对数据流量进行实时分析,并对各种方式进行检测,检测引擎后发出报警信息。利用SNMP传感器获取网络拓扑图;使用NetFlow传感器获取网络连接信息。对无线网络安全态势的风险度进行模糊子集的模糊划分,设计安全态势动态预测的流程。由试验结果可知,该系统最高输入信号频谱为20 mV,最低输入信号频谱为-17 mV,与选取的100组态势数据时序图一致,表明该系统预测结果精准。

In order to solve the problems of untimely prediction behavior and inaccurate prediction results in the process of existing methods to predict wireless network security situation,a wireless network security situation prediction system based on fuzzy logic is proposed. Log sensors are used to obtain relevant parameters and remove a large number of redundant data. The Snort intrusion detection system is used to analyze the data flow in real time,detect various methods,and send alarm information after the detection engine. Using SNMP sensor to obtain network topology;Use NetFlow sensors to obtain network connection information. The risk degree of wireless network security situation is divided into fuzzy subsets,and the process of dynamic prediction of security situation is designed. It can be seen from the test results that the maximum input signal spectrum of the system is 20 mV,and the minimum input signal spectrum is-17 mV,which is consistent with the timing chart of 100 groups of situation data selected,indicating that the prediction results of the system are accurate.