工业信息物理系统间隙DoS攻击的自适应事件触发稳定控制

孙子文, 刘加磊

doi:10.12141/j.issn.1000-565X.220084

华南理工大学学报(自然科学版) >

2023 , Vol. 51 >Issue 3: 146 - 156

DOI: https://doi.org/10.12141/j.issn.1000-565X.220084

电子、通信与自动控制

工业信息物理系统间隙DoS攻击的自适应事件触发稳定控制

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^1.江南大学物联网工程学院，江苏无锡 214122
^2.物联网技术应用教育部工程研究中心，江苏无锡 214122

孙子文（1968-），女，博士，教授，主要从事控制理论与控制工程、模式识别、人工智能、无线传感网络理论与技术和信息安全等研究。

收稿日期: 2022-02-28

网络出版日期: 2022-09-13

基金资助

国家自然科学基金资助项目(62173160)

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Adaptive Event-Triggered Stability Control for Intermittent DoS Attacks in Industrial Cyber Physical Systems

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^1.School of Internet of Things Engineering，Jiangnan University，Wuxi 214122，Jiangsu，China
^2.Engineering Research Center of Internet of Things Technology Applications Ministry of Education，Wuxi 214122，Jiangsu，China

孙子文（1968-），女，博士，教授，主要从事控制理论与控制工程、模式识别、人工智能、无线传感网络理论与技术和信息安全等研究。

Received date: 2022-02-28

Online published: 2022-09-13

Supported by

the National Natural Science Foundation of China(62173160)

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摘要

针对具有间隙拒绝服务（DoS）攻击的工业信息物理系统（ICPS），研究一种基于观测器的自适应事件触发稳定控制方案。首先构造一个观测器估计系统状态，并采用一种新的自适应事件触发通信方案以节约网络资源；然后通过受频率和持续时间限制的间隙DoS攻击对ICPS的影响建立攻击模型，将受到DoS攻击的ICPS划分为DoS攻击活跃期系统和DoS攻击休眠期系统，并用一些过去成功触发状态重构当前受到攻击的状态，得到基于动态估计器的攻击补偿机制，保证系统在DoS攻击活跃期间的渐进稳定；最后运用分段Lyapunov泛函方法、Jensen’s不等式和Schur补引理，得到系统的稳定条件，并提出自适应事件触发参数、观测器增益和控制器增益的协同设计方案。用间歇反应器系统模拟间隙DoS攻击下基于自适应事件触发的ICPS系统稳定性能。仿真结果表明，自适应事件触发策略和基于动态估计器的补偿机制不仅能够提升系统的稳定性，还能有效降低数据传输的次数，系统在静态事件触发策略下的触发次数大约是在自适应事件触发策略下的4.5倍。

关键词： 工业信息物理系统; 间隙拒绝服务攻击; 自适应事件触发; 稳定控制; 状态重构; 观测器

本文引用格式

孙子文, 刘加磊 . 工业信息物理系统间隙DoS攻击的自适应事件触发稳定控制[J]. 华南理工大学学报(自然科学版), 2023 , 51(3) : 146 -156 . DOI: 10.12141/j.issn.1000-565X.220084

Abstract

For industrial information physical systems (ICPS) with gap denial of service (DoS) attacks, an observer-based adaptive event-triggered stability control scheme was proposed. Firstly, an observer was constructed to estimate the unmeasured state of the system, and a new adaptive event-triggered communication scheme was adopted to save network resources. Secondly, an attack model was established based on the influence of intermittent DoS attacks on ICPS limited by frequency and duration. ICPS subjected to DoS attacks was divided into active DoS attack system and dormant DoS attack system, and the current attacked states were reconstructed by some successful trigger states. An attack compensation mechanism based on dynamic estimator was proposed to ensure the asymptotic stability of the system during active DoS attacks. Finally, the piecewise Lyapunov functional method, Jensen’s inequality and Schur’s complement lemma were used to obtain the stability conditions of the system. On this basis, a cooperative design scheme of adaptive event triggering parameters, observer gain and controller gain was proposed. The intermittent reactor system was used to simulate the stability of ICPS based on adaptive event triggering under intermittent DoS attack. The simulation results show that the adaptive event triggering strategy and the compensation mechanism based on the dynamic estimator can not only improve the stability of the system, but also effectively reduce the number of data transmission. The times of the system triggered by the static event triggering policy is about 4.5 times that of the system triggered by the adaptive event triggering policy.

Key words： industrial cyber physical system; DoS attack; adaptive event-triggered; stability control; reconstructed states; observer

参考文献

1	王中杰，谢璐璐．信息物理融合系统研究综述［J］．自动化学报，2011，37（10）：1157-1166.
	WANG Zhongjie， XIE Lulu ．Cyber-physical systems：A survey［J］．Acta Automatica Sinica，2011，37（10）：1157-1166.
2	WALSH G C， YE H ．Scheduling of networked control systems［J］．IEEE Control Systems，2001，21（1）：57-65.
3	MAHMOUD M S， HAMDAN M M， BARUDI U A ．Modeling and control of cyber-physical systems subject to cyber attacks：A survey of recent advances and challenges［J］．Neurocomputing，2019，338（21）：101-115.
4	LANGNER R ．Stuxnet：dissecting a cyberwarfare weapon［J］．IEEE Security and Privacy Magazine，2011，15（1）：49-51.
5	汤奕，陈倩，李梦雅，等．电力信息物理融合系统环境中的网络攻击研究综述［J］．电力系统自动化，2016，40（17）：59-69.
	TANG Yi， CHEN Qian， LI Mengya，et al ．Review of network attack research in power information physical fusion system environment［J］．Automation of Electric Power Systems，2016，40（17）：59-69.
6	FAWZI H， TABUADA P， DIGGAVI S ．Secure estimation and control for cyber-physical systems under adversarial attacks［J］．IEEE Transactions on Automatic Control，2014，59（6）：1454-1467.
7	YANG X， KONG L S， LIU Z，et al ．Machine learning and deep learning methods for cyber security［J］．IEEE Access，2018，6：35365-35381.
8	CHAUDHARI R S， TALMALE G R ．A review on detection approaches for distributed denial of service attacks［C］∥Proceedings of the 2019 International Conference on Intelligent Sustainable Systems （ICISS）．Palladam：IEEE，2019：323-327.
9	MURUGAN K， SURESH P ．Efficient anomaly intrusion detection using hybrid probabilistic techniques in wireless ad hoc network［J］．International Journal of Network Security，2018，20（4）：730-737.
10	BUCZAK A L， GUVEN E ．A survey of data mining and machine learning methods for cyber security intrusion detection［J］．IEEE Communications Surveys and Tutorials，2017，18（2）：1153-1176.
11	AHMED M， MAHMOOD A N， HU J K ．A survey of network anomaly detection techniques［J］．Journal of Network and Computer Applications，2016，60：19-31.
12	庄康熙，孙子文．针对工业信息物理系统中的拒绝服务攻击建立检测模型［J］．控制理论与应用，2020，37（3）：629-638.
	ZHUANG Kangxi， SUN Ziwen ．Establishing a detection model for denial of service attacks in industrial cyber physical systems［J］．Control Theory Applications，2020，37（3）：629-638.
13	PERSIS C D， TESI P ．Input-to-state stabilizing control under denial-of-service［J］．IEEE Transactions on Automatic Control，2015，60（11）：2930-2944.
14	FENG S， TESI P ．Networked control systems under denial-of-service：co-located vs．remote architectures［J］．Systems & Control Letters，2017，108：40-47.
15	FENG S， TESI P ．Resilient control under denial-of-service：Robust design［J］．Automatica，2017，79：42-51.
16	汪慕峰，胥布工．DoS攻击下的一类信息物理系统保性能控制［J］．华南理工大学学报（自然科学版），2018，46（8）：19-26.
	WANG Mufeng， XU Bugong ．Guaranteed cost control for a class of cyber-physical systems under DoS attacks［J］．Journal of South China University of Technology （Natural Science Edition），2018，46（8）：19-26.
17	XING W， SHI P， AGARWAL R K，et al ．Robust H∞ pinning synchronization for complex networks with event-triggered communication scheme［J］．IEEE Transactions on Circuits and Systems I：Regular Papers，2020，69（12）：5233-5245.
18	HEEMELS W， DONKERS M ．Periodic event-triggered control for linear systems［J］．IEEE Transactions on Automatic Control，2013，49（3）：698-711.
19	HU S， YUE D， XIE X，et al ．Resilient event-triggered controller synthesis of networked control systems under periodic DoS jamming attacks［J］．IEEE Transactions on Cybernetics，2019，49（12）：4271-4281.
20	YIN T， ZHA L， LIU J，et al ．Adaptive event-triggered controller design for cyber-physical systems with complex cyber-attacks［C］∥Proceedings of the 2019 Chinese Automation Congress （CAC）．Hangzhou：IEEE，2019：4202-4207.
21	ZHAO N， SHI P， XING W，et al ．Observer-based event-triggered approach for stochastic networked control systems under denial of service attacks［J］．IEEE Transactions on Control of Network Systems，2021，8（1）：158-167.
22	WANG P B， REN X M， ZHENG D D ．Event-triggered resilient control for cyber-physical systems under periodic DoS jamming attacks［J］．Information Sciences，2021，577：541-556.
23	HU S L， YUE D， CHENG Z，et al ．Co-design of dynamic event triggered communication scheme and resilient observer-based control under aperiodic DoS attacks［J］．IEEE Transactions on Cybernetics，2021，51（9）：4591-4601.
24	HU S L， GU Y， CHEN X，et al ．Observer-based event-triggered control for cyber-physical systems under unknown periodic DoS jamming attacks［C］∥Proceedings of the 2018 Chinese Control and Decision Conference （CCDC）．Shenyang：IEEE，2018：1422-1427.

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