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工业互联网流量分析技术综述

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为了深入理解流量分析技术在工业互联网中的应用,基于流量分析的5个主要步骤阐述了工业互联网区别于传统互联网的独特性.同时,通过调研大量相关研究工作,总结了流量预测、协议识别与逆向、工业资产指纹识别、入侵检测、加密流量识别和漏洞挖掘6个主流研究任务,并根据任务性质将其分类为面向服务质量提高和面向安全能力提升的2类应用,充分挖掘了工业互联网中的流量分析技术应用场景.最后,针对流量分析未来进一步应用于工业互联网所面临的挑战进行了讨论,并展望了潜在的研究方向.
Survey of industrial Internet traffic analysis technology
To gain an in-depth awareness of the application of traffic analysis technology in the industrial Internet,the dif-ferences between the industrial Internet and the traditional Internet through the five core traffic analysis processes were il-lustrated.By reviewing a large number of related papers,the application of six popular were summarized in the industrial Internet,such as traffic prediction,protocol identification and reverse engineering,industrial asset fingerprinting,intru-sion detection,encrypted traffic identification and vulnerability mining.Depending on the nature of the task,traffic analysis technology was classified into two types of applications,such as service quality enhancement and security capa-bility development,allowing to thoroughly explore the application scenarios of traffic analysis technology in the indus-trial Internet.Finally,the challenges associated with future traffic analysis applications in the industrial Internet were ex-amined,as well as potential development possibilities.

industrial Internetindustrial control systemtraffic analysismachine learning

刘奇旭、肖聚鑫、谭耀康、王承淳、黄昊、张方娇、尹捷、刘玉岭

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中国科学院信息工程研究所,北京 100085

中国科学院大学网络空间安全学院,北京 100049

工业互联网 工业控制系统 流量分析 机器学习

中国科学院青年创新促进会项目国家电网科技基金中国科学院网络测评技术重点实验室和网络安全防护技术北京市重点实验室项目

SG270000YXJS2311060

2024

通信学报
中国通信学会

通信学报

CSTPCD北大核心
影响因子:1.265
ISSN:1000-436X
年,卷(期):2024.45(8)