基于数字孪生的工业互联网安全检测与响应研究

马佳利; 郭渊博; 方晨; 陈庆礼; 张琦

doi:10.11959/j.issn.1000-436x.2024091

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基于数字孪生的工业互联网安全检测与响应研究

专题：工业互联网安全技术 | 更新时间：2024-08-08

- 基于数字孪生的工业互联网安全检测与响应研究
- Research on industrial Internet security detection and response based on digital twin
- 通信学报 2024年45卷第6期页码：87-100
- 作者机构：
  
  信息工程大学密码工程学院，河南郑州 450001
- 作者简介：
  
  [ "马佳利（1996- ），男，福建福清人，信息工程大学博士生，主要研究方向为数字孪生、网络安全、工业互联网等。" ]
  [ "郭渊博（1975- ），男，陕西周至人，博士，信息工程大学教授、博士生导师，主要研究方向为网络安全、数据挖掘、机器学习和人工智能安全等。" ]
  [ "方晨（1993- ），男，安徽宿松人，博士，信息工程大学讲师，主要研究方向为机器学习、隐私安全等。" ]
  陈庆礼（1998- ），男，河南新乡人，信息工程大学硕士生，主要研究方向为人工智能安全等。
  张琦（1983- ），男，河南新乡人，信息工程大学副教授，主要研究方向为人工智能安全等。
- 基金信息：
  
  国家自然科学基金资助项目(62276091);国家社会科学基金资助项目(2022-SKJJ-B-057);河南省重大公益专项基金资助项目;Major Public Welfare Project of Henan Province(201300311200)
- DOI：10.11959/j.issn.1000-436x.2024091
  中图分类号： TP391
- 收稿：2023-11-13，
  
  修回：2024-04-08，
  
  纸质出版：2024-06-25
- 稿件说明：
移动端阅览
马佳利,郭渊博,方晨等.基于数字孪生的工业互联网安全检测与响应研究[J].通信学报,2024,45(06):87-100.

MA Jiali,GUO Yuanbo,FANG Chen,et al.Research on industrial Internet security detection and response based on digital twin[J].Journal on Communications,2024,45(06):87-100.
马佳利,郭渊博,方晨等.基于数字孪生的工业互联网安全检测与响应研究[J].通信学报,2024,45(06):87-100. DOI： 10.11959/j.issn.1000-436x.2024091.

MA Jiali,GUO Yuanbo,FANG Chen,et al.Research on industrial Internet security detection and response based on digital twin[J].Journal on Communications,2024,45(06):87-100. DOI： 10.11959/j.issn.1000-436x.2024091.

摘要

考虑传统网络安全防御方法不能够满足工业互联网对可靠性和稳定性的严格要求，基于数字孪生的思想研究了一种在数字空间中通过采集现场数据和使用孪生模型安全认知进行异常检测和响应的方法。首先，通过对数字孪生建模方案进行分析，总结出4类建模方法并集成到多模块数字孪生（DT）架构中；然后，通过引入信号时序逻辑技术将不同孪生模型认知转化为标准的信号时序逻辑（STL）规范集，根据规范集对系统行为的监测实现异常检测，多源认知增加了检测结果的可靠性；最后，通过对违反STL规范集情况的分析实现异常定位，并通过对已知设备故障的分析设计相应STL弱规范实现异常分类，对异常的两方面响应有利于帮助系统恢复正常运行。案例研究表明，所提方法在异常检测和响应方面非常有效。将所提方法与基于深度学习的入侵检测系统进行对比，实验结果表明，所提方法在对异常情况的检测时检出率提高了25%~40.9%。

Abstract

Considering that traditional network security defense methods cannot meet the strict requirements of industrial Internet for reliability and stability

a method for anomaly detection and response in digital space was studied based on the idea of digital twins by collecting on-site data and using twin model security cognition. Firstly

four types of modeling methods were summarized and integrated into the multi module digital twin (DT) architecture by analyzing the digital twin modeling solutions. Secondly

the cognition of different twin models was transformed into a standard signal temporal logic (STL) specification set by introducing signal temporal logic technology

and anomaly detection was achieved by monitoring system behavior based on the specification set

by the reliability of detection results was increased. Finally

anomaly localization was achieved through the analysis of violations of the STL specification set

and corresponding STL weak specifications were designed through the analysis of known device faults to achieve anomaly classification. Two aspects of response to anomalies were beneficial for helping the system restore normal operation. The case study demonstrates that the effectiveness of the proposed method in anomaly detection and response. Comparing the proposed method with the intrusion detection system based on deep learning

the experimental results show that the detection rate of the proposed method increases by 25%~40.9% in detecting anomalies.

关键词

Keywords

references

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