Iteration-Form Multiplicative Watermarking for Quantization-Involved Networked Control Systems

IF 9.9 1区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS
Changda Zhang;Dajun Du;Xue Li;Changchun Hua
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引用次数: 0

Abstract

Multiplicative watermarking can enhance cyber attacks detection capacity of quantization-involved networked control system (QNCSs). This article presents an iteration-form solution to conventional summation-form multiplicative watermarking (SMW). First, limitation of conventional SMW for QNCSs is revealed, where there exists high design complexity whilst decreasing measurement perturbation from SMW and achieving successful replay attacks (RAs) detection. Second, a new iteration-form multiplicative watermarking (IMW) is designed by leveraging a keys transformation to reconstruct SMW with multiple coupled keys, where design complexity is greatly reduced and there are only dual decoupled keys to be designed. Furthermore, a positive correlation between value of one key and measurement perturbation from IMW is provided. Third, a positive correlation between ratio of the other key at different instants and RAs detection performance of IMW is explored by using residual covariance analysis. Finally, experimental results from networked inverted pendulum systems confirm the feasibility and effectiveness of new IMW.
涉及量化的网络控制系统的迭代形式乘法水印
乘性水印可以提高量化网络控制系统的网络攻击检测能力。本文提出了一种迭代形式的传统求和形式乘法水印(SMW)解决方案。首先,揭示了传统SMW在qncs中存在的局限性,即在降低SMW的测量扰动并成功检测重放攻击(RAs)的同时,存在较高的设计复杂度。其次,利用密钥变换,设计了一种新的迭代形式的乘法水印(IMW),通过多个耦合密钥重构SMW,大大降低了设计复杂度,只需设计双解耦密钥。此外,给出了一个键值与测量扰动之间的正相关关系。第三,利用残差协方差分析探讨了不同时刻其他键的比值与IMW的RAs检测性能之间的正相关关系。最后,通过网络化倒立摆系统的实验验证了该方法的可行性和有效性。
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来源期刊
IEEE Transactions on Industrial Informatics
IEEE Transactions on Industrial Informatics 工程技术-工程:工业
CiteScore
24.10
自引率
8.90%
发文量
1202
审稿时长
5.1 months
期刊介绍: The IEEE Transactions on Industrial Informatics is a multidisciplinary journal dedicated to publishing technical papers that connect theory with practical applications of informatics in industrial settings. It focuses on the utilization of information in intelligent, distributed, and agile industrial automation and control systems. The scope includes topics such as knowledge-based and AI-enhanced automation, intelligent computer control systems, flexible and collaborative manufacturing, industrial informatics in software-defined vehicles and robotics, computer vision, industrial cyber-physical and industrial IoT systems, real-time and networked embedded systems, security in industrial processes, industrial communications, systems interoperability, and human-machine interaction.
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