基于特征库识别法的移动通信网络异常流量监测系统

Abnormal Traffic Monitoring Method in Mobile Communication Network Based on Feature Library Recognition

针对传统的异常流量监测系统在监测移动通信网络流量时存在监测结果准确度不高的情况,提出一种基于特征库识别的移动通信网络异常流量监测方法,对移动通信网络异常流量监测系统的硬件和软件进行设计。硬件部分分为三个子系统,分别为采集系统、监测系统和显示系统,重点设计了采集系统和监测系统。根据硬件结构给出了软件流程图,通过阈值设定、流量监测、数据统计三步完成整个工作过程。与传统监测系统进行实验对比,结果表明,运用特征库识别法设计的移动通信网络异常流量监测系统能够有效保证监测结果准确性,具有较高的使用价值。

Aiming at the inaccuracy of the traditional abnormal traffic monitoring system in monitoring mobile communication network traffic, this paper proposes a method of abnormal traffic monitoring in mobile communication network based on feature library recognition. The hardware and software of abnormal traffic monitoring system in mobile communication network are designed. The hardware part is divided into three subsystems, which are acquisition system, monitoring system and display system. The acquisition system and monitoring system are mainly designed. The software flow chart is given according to the hardware structure, and the whole work process is completed by three steps: threshold setting, flow monitoring and data statistics. Compared with the traditional monitoring system, the results show that the anomalous traffic monitoring system based on feature library recognition method can effectively improve the accuracy of monitoring results, and has a high value of use.