校园网流量异常检测与处理方法

摘要

With the scaling and complicating of the campus network, more and more security threats, network attacks due to network traffic and other factors led to differences occur, abnormal Flow detection and treatment is becoming increasingly important. This exception to the campus network abnormal Flow classification, analysis of the production of various abnormal traffic, and proposes the corresponding detection and treatment methods) Attacks against the current exception handling methods to solve the shortcomings, to design a campus network anomaly detection and cleaning model to improve the campus network Flow exception handling capacity to ensure normal business campus users are not affected.%随着校园网日益规模化和复杂化,校园网安全威胁越来越严重,因网络攻击等因素导致网络流量异常时有发生,流量异常检测与处理显得日益重要.本文对校园网络中流量异常进行分类,分析产生各种流量异常的原因,并提出相应的检测与处理方法；针对目前网络攻击异常处理方法存在的不足,从确保校园用户正常业务不受任何影响的前提出发,设计出一种校园网异常流量检测与清洗模型,提高校园网络流量异常处理能力.