| 基于专家经验的网络异常流量自动检测平台设计与实现 |
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| 引用本文：黄自力1,2，潘孝闻1,2，杨阳1,2.基于专家经验的网络异常流量自动检测平台设计与实现[J].计算技术与自动化,2025,(2):161-165 |
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| 中文摘要:随着网络流量规模的日益增大，异常流量越来越多。传统基于规则的异常流量检测效果不尽理想，而专家的人工分析又会消耗大量的时间与极高的人力成本，为此，本文基于专家经验设计并实现了一个网络异常流量自动检测平台，以此降低人工分析的工作量。检测平台通过机器学习、词法分析的方法，自动收集流量特征，同时对正常与恶意HTTP流量进行分析，从而有效地检测出异常流量。实验结果表明，相比于传统WAF，本文设计的自动检测平台检出率更高，误判率更低。 |
| 中文关键词:流量检测 专家经验 机器学习 词法分析 |
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| Design and Implementation of Automatic Detection Platform for Network Abnormal Traffic Based on Expert Experience |
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| Abstract:With the increasing scale of network traffic, more and more abnormal traffic is generated. Traditional rule based abnormal traffic detection is not ideal, and manual analysis by experts will consume a lot of time and high labor costs. Therefore, this paper designs and implements an automatic detection platform for network abnormal traffic based on expert experience to reduce workload of manual analysis. By means of machine learning and lexical analysis the detection platform collects traffic features automatically and analyzes normal and malicious HTTP traffic respectively so as to detect abnormal traffic effectively. The experiment results comparing with traditional web application firewall shows that the automatic detection platform proposed by this paper can reduce workload of manual analysis and has higher positive rate and lower misjudgment rate. |
| keywords:traffic detection expert experience machine learning lexical analysis |
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