基于大数据技术的光纤通信网络异常流量动态检测方法

Dynamic Detection Method for Abnormal Traffic in Optical Communication Networks Based on Big Data Technology

随着大数据技术的飞速发展,光纤通信网络作为信息传输的重要载体,其安全性与稳定性受到了广泛关注。特别是在大数据环境下,光纤通信网络中的数据流量巨大、类型多样,异常流量的出现会导致网络拥堵、资源占用过多,对网络安全构成严重威胁。因此,对光纤通信网络中的异常流量进行动态检测与分析,成为当前网络安全领域急待解决的问题。本研究中,基于大数据技术分析光纤通信网络异常流量动态检测方法与具体的对策。

With the rapid development of big data technology,optical fiber communication networks,as an important carrier of information transmission,have received widespread attention for their security and stability.Especially in the context of big data,the data traffic in optical fiber communication networks is huge and diverse,and the emergence of abnormal traffic can lead to network congestion,excessive resource utilization,and pose a serious threat to network security.Therefore,dynamic detection and analysis of abnormal traffic in optical fiber communication networks have become an urgent issue to be addressed in the field of network security.In this study,based on the big data environment,the dynamic detection methods and specific countermeasures of abnormal traffic in optical fiber communication networks are analyzed.