Optimal strategy of data tampering attacks for FIR system identification with average entropy and binary-valued observations

IF 3.9 4区计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS

International Journal of Adaptive Control and Signal Processing Pub Date : 2024-07-18 DOI:10.1002/acs.3877

Zhongwei Bai, Yan Liu, Yinghui Wang, Jin Guo

引用次数: 0

Abstract

In the era of digitalization boom, cyber-physical system (CPS) has been widely used in several fields. However, malicious data tampering in communication networks may lead to degradation of the state estimation performance, which may affect the control decision and cause significant losses. In this paper, for the identification of finite impluse response (FIR) systems with binary-valued observations under data tampering attack, an optimal attack strategy based on the average entropy is designed from the perspective of the attacker. In the case of unknown parameters, the regression matrix is used to give the estimation method of the system parameters, the algorithmic flow of the data tampering attack for the implementation of the on-line attack is designed. Finally, the effectiveness of the algorithm and the reliability of the conclusions is verified through the examples.

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利用平均熵和二值观测数据识别 FIR 系统的最佳数据篡改攻击策略

摘要在数字化蓬勃发展的时代，网络物理系统（CPS）已被广泛应用于多个领域。然而，通信网络中的恶意数据篡改可能会导致状态估计性能下降，从而影响控制决策并造成重大损失。本文针对数据篡改攻击下观测值为二值的有限隐含响应（FIR）系统的识别问题，从攻击者的角度出发，设计了一种基于平均熵的最优攻击策略。在参数未知的情况下，利用回归矩阵给出了系统参数的估计方法，设计了实现在线攻击的数据篡改攻击算法流程。最后，通过实例验证了算法的有效性和结论的可靠性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of Adaptive Control and Signal Processing 工程技术-工程：电子与电气

CiteScore

5.30

自引率

16.10%

发文量

163

审稿时长

5 months

期刊介绍： The International Journal of Adaptive Control and Signal Processing is concerned with the design, synthesis and application of estimators or controllers where adaptive features are needed to cope with uncertainties.Papers on signal processing should also have some relevance to adaptive systems. The journal focus is on model based control design approaches rather than heuristic or rule based control design methods. All papers will be expected to include significant novel material. Both the theory and application of adaptive systems and system identification are areas of interest. Papers on applications can include problems in the implementation of algorithms for real time signal processing and control. The stability, convergence, robustness and numerical aspects of adaptive algorithms are also suitable topics. The related subjects of controller tuning, filtering, networks and switching theory are also of interest. Principal areas to be addressed include: Auto-Tuning, Self-Tuning and Model Reference Adaptive Controllers Nonlinear, Robust and Intelligent Adaptive Controllers Linear and Nonlinear Multivariable System Identification and Estimation Identification of Linear Parameter Varying, Distributed and Hybrid Systems Multiple Model Adaptive Control Adaptive Signal processing Theory and Algorithms Adaptation in Multi-Agent Systems Condition Monitoring Systems Fault Detection and Isolation Methods Fault Detection and Isolation Methods Fault-Tolerant Control (system supervision and diagnosis) Learning Systems and Adaptive Modelling Real Time Algorithms for Adaptive Signal Processing and Control Adaptive Signal Processing and Control Applications Adaptive Cloud Architectures and Networking Adaptive Mechanisms for Internet of Things Adaptive Sliding Mode Control.