工业互联网流量分析技术综述

刘奇旭; 肖聚鑫; 谭耀康; 王承淳; 黄昊; 张方娇; 尹捷; 刘玉岭

doi:10.11959/j.issn.1000-436x.2024145

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工业互联网流量分析技术综述

综述 | 更新时间：2024-09-10

- 工业互联网流量分析技术综述
- Survey of industrial Internet traffic analysis technology
- 通信学报 2024年45卷第8期页码：221-237
- 作者机构：
  
  1.中国科学院信息工程研究所，北京 100085
  2.中国科学院大学网络空间安全学院，北京 100049
- 作者简介：
  
  [ "刘奇旭（1984- ），男，江苏徐州人，博士，中国科学院信息工程研究所研究员，中国科学院大学教授，主要研究方向为网络攻防技术、网络安全评测。" ]
  [ "肖聚鑫（1999- ），男，江西萍乡人，中国科学院大学博士生，主要研究方向为网络攻防技术、物联网安全、网络流量分析等。" ]
  [ "谭耀康（1998- ），男，广东肇庆人，中国科学院大学硕士生，主要研究方向为Web安全、程序分析。" ]
  [ "王承淳（2000- ），男，山东济南人，中国科学院大学博士生，主要研究方向为异常流量检测、恶意软件分析等。" ]
  [ "黄昊（2001- ），男，江西九江人，中国科学院大学博士生，主要研究方向为Web安全、AI安全等。" ]
  [ "张方娇（1989- ），女，山东泰安人，博士，中国科学院信息工程研究所高级工程师，主要研究方向为Web安全、溯源取证等。" ]
  [ "尹捷（1991- ），女，重庆人，博士，中国科学院信息工程研究所工程师，主要研究方向为恶意代码对抗、僵尸网络、物联网安全等。" ]
  [ "刘玉岭（1982- ），男，山东济阳人，博士，中国科学院信息工程研究所正高级工程师，主要研究方向为网络安全测评和等级保护。" ]
- 基金信息：
  
  中国科学院青年创新促进会基金资助项目;国家电网有限公司科技基金资助项目(SG270000YXJS2311060);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基金资助项目
- DOI：10.11959/j.issn.1000-436x.2024145
  中图分类号： TP393
- 收稿日期：2024-03-07，
  
  修回日期：2024-07-22，
  
  纸质出版日期：2024-08-25
- 稿件说明：
移动端阅览
刘奇旭,肖聚鑫,谭耀康等.工业互联网流量分析技术综述[J].通信学报,2024,45(08):221-237.

LIU Qixu,XIAO Juxin,TAN Yaokang,et al.Survey of industrial Internet traffic analysis technology[J].Journal on Communications,2024,45(08):221-237.
刘奇旭,肖聚鑫,谭耀康等.工业互联网流量分析技术综述[J].通信学报,2024,45(08):221-237. DOI： 10.11959/j.issn.1000-436x.2024145.

LIU Qixu,XIAO Juxin,TAN Yaokang,et al.Survey of industrial Internet traffic analysis technology[J].Journal on Communications,2024,45(08):221-237. DOI： 10.11959/j.issn.1000-436x.2024145.

摘要

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。

Abstract

To gain an in-depth awareness of the application of traffic analysis technology in the industrial Internet

the differences between the industrial Internet and the traditional Internet through the five core traffic analysis processes were illustrated. 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

intrusion 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 capability development

allowing to thoroughly explore the application scenarios of traffic analysis technology in the industrial Internet. Finally

the challenges associated with future traffic analysis applications in the industrial Internet were examined

as well as potential development possibilities.

关键词

Keywords

references

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