工控网络异常流量攻击自动溯源方法研究  

Research on Automatic Tracing Method of Abnormal Traffic Attack in Industrial Control Network

作　　者：邓广龙 张迁礼 牛健 DENG Guanglong;ZHANG Qianli;NIU Jian(Intelligent Manufacturing Institute,Heilongjiang Academy of Sciences,Harbin 150090,China)

机构地区：[1]黑龙江省科学院智能制造研究所,哈尔滨150090

出　　处：《自动化与仪表》2025年第4期148-152,161,共6页Automation & Instrumentation

摘　　要：该文对工控网络中网络异常流量攻击溯源的准确性低的问题进行了研究,进行了国内外相关研究分析,采用瑞丽熵和赫斯特指数相结合方法,构建了瑞丽熵和赫斯特指数的网络流量异常流量攻击检测算法,并在该基础上构建溯源算法。基于利用瑞丽熵比值对网络异常攻击进行检测和溯源是创新之处。经实验测试,实现了将工控系统异常网络流量攻击检测和溯源准确率提高的目的,试验结果发现检测算法的准确率为98.7%,溯源算法有效地追踪到攻击源。This paper studies the low accuracy of network abnormal traffic attack tracing in industrial control networks,and analyzes relevant researches at home and abroad.A network abnormal traffic attack detection algorithm based on Renyi entropy and Hurst index is constructed by combining the method of Renyi entropy and Hurst index.It is innovative to detect and trace network anomaly attacks based on Rayleigh entropy ratio.The experiment results show that the accuracy of detecting and tracing abnormal network traffic attacks in industrial control system is 98.7%,and the tracing algorithm can track the attack source effectively.

关 键 词：工控网络 瑞丽熵 赫斯特指数 异常流量攻击 溯源 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]