【作者】 秦辉东； 杨加； 金建栋； 李笑难； 马皓；

【Author】 QIN Huidong;YANG Jia;JIN Jiandong;Li Xiaonan;MA Hao;Computer Center,Peking University;

【机构】 北京大学计算中心；

【摘要】 近年来,针对高校网络的攻击事件频发,包括DDoS攻击、木马病毒、挖矿病毒等多种形式,给校园网络安全造成很大的危害。对于这些突发网络事件,目前的校园网络系统无法快速地识别和诊断。针对校园网络环境下实际存在的这些问题,设计基于ELK Stack的实时校园网络监控平台,基于请求链接、流入/流出流量、IP地址类型等指标,实现对校园网络流量数据、运行态势的实时监控,及时发现校园网络出现的异常。通过构建的大数据风险模型,完成实时风险预警。更多还原

【Abstract】 In recent years,there has been a surge in cyber attacks targeting university networks,including DDoS attacks,Trojan viruses,and cryptojacking malware,resulting in significant harm to campus network security.The current campus network systems are unable to quickly identify and diagnose these sudden network incidents.To address these issues present in the campus network environment,a real-time campus network monitoring platform based on the ELK Stack has been designed.By utilizing metrics such as request links,inbound/outbound traffic,and IP address types,this platform enables real-time monitoring of campus network traffic data and operational trends,allowing for timely detection of network anomalies.With the construction of a comprehensive big data risk model,real-time risk alerts can be realized.更多还原