摘要
传统感知系统采集的流量数据属性,与网络态势关联程度不大,导致预测网络态势值存在误差。为此,提出基于智慧校园的网络态势感知系统。硬件方面,构建智慧校园网络框架,以嵌入式微处理器为中心,优化感知网关,连接智慧校园终端设备与服务器;软件方面,对数据流设置时间窗口,预处理后采集数据属性,判断存在异常的数据包,对其进行聚合整理,计算异常数据流发生可能性、威胁性,赋值校园网络防御能力,计算网络态势值,感知网络安全程度。为主机分配脆弱性数据和恶意代码数据,进行对比实验,结果表明,此次设计系统提高了攻击数据检测率,缩短了网络态势值预测时间,同时降低了预测误差,保证了网络态势感知精度。
the attribute of traffic data collected by traditional perception system has little correlation with network situation,which leads to errors in predicting network situation.Therefore,a network situation awareness system based on smart campus is proposed.In terms of hardware,the framework of smart campus network is constructed,with embedded microprocessor as the center,the perception gateway is optimized,and the smart campus terminal equipment and server are connected;in terms of software,the time window is set for the data flow,the data attributes are collected after preprocessing,the abnormal packet data is judged,the aggregation is carried out,the possibility and threat of abnormal data flow are calculated,and the value is assigned Campus network defense capability,network situation value calculation,network security awareness.The system allocates vulnerability data and malicious code data to the host,and carries out comparative experiments.The results show that the system improves the detection rate of attack data,shortens the prediction time of network situation value,reduces the prediction error,and ensures the accuracy of network situation awareness.
作者
廖信海
LIAO Xinghai(Guangdong University of Foreign Studies,Guangzhou 510000,China)
出处
《自动化与仪器仪表》
2021年第8期139-142,共4页
Automation & Instrumentation
基金
基于“等保2.0”规范搭建网络空间安全体系实训教学环境的研究(No.GWJ20195513)。
关键词
智慧校园
感知网关
异常数据流
态势值
防御能力
smart campus
perception gateway
abnormal data flow
situation value
defense capability
作者简介
廖信海(1976-),男,湖南郴州人,硕士研究生,副主任,主要研究方向为数据中心与网络运维。
