文献类型：期刊文献

英文题名：Secure remote state estimation against linear man-in-the-middle attacks using watermarking

作者：Huang, Jiahao[1];Ho, Daniel W. C.[2];Li, Fangfei[1,3];Yang, Wen[1];Tang, Yang[1]

机构：[1]East China Univ Sci & Technol, Key Lab Adv Control & Optimizat Chem Proc, Minist Educ, Shanghai 200237, Peoples R China;[2]City Univ Hong Kong, Dept Math, Kowloon, Hong Kong, Peoples R China;[3]East China Univ Sci & Technol, Dept Math, Shanghai 200237, Peoples R China

年份：2020

卷号：121

外文期刊名：AUTOMATICA

收录：;EI(收录号：20203209025001);WOS:【SCI-EXPANDED(收录号:WOS:000571445600007)】；

基金：This work was supported by the National Natural Science Foundation of China (Grant Nos. 61988101, 61751305, 61673176, 61973123, 61773161), the Science and Technology Commission of Shanghai Municipality under Grant 18ZR1409800, the Fundamental Research Funds for the Central Universities, the Research Grants Council of the Hong Kong Special Administrative Region (Grant Nos. CityU 11202819, CityU 11200717), and the Programme of Introducing Talents of Discipline to Universities (the 111 Project) under Grant B17017.

语种：英文

外文关键词：Cyber-physical systems; Cyber security; Man-in-the-middle attack; Remote state estimation; Watermarking

摘要：In this paper, an attack defense method is proposed to address the secure remote state estimation problem caused by linear man-in-the-middle attacks in cyber-physical systems (CPS). We utilize the pseudo-random number as a watermarking to encrypt and decrypt the data transmitted through the wireless network. Via the proposed method, the transmitted data in the normal operation can be recovered. Since the data modified by the attacker can be marked with the watermarking, the chi(2) detector is capable of detecting the attack. For three different attack scenarios, we analyze the evolution of the remote estimation error covariances and the detection performance, respectively. In the sense of minimizing the estimation error covariance, the optimal parameter set of the watermarking is derived. Furthermore, the proposed method can even be extended to detect the false data injection attack and the replay attack. Finally, several examples are provided to illustrate the derived results. (C) 2020 Elsevier Ltd. All rights reserved.