文献类型：期刊文献

英文题名：Distributed filtering under false data injection attacks

作者：Yang, Wen[1];Zhang, Yu[1];Chen, Guanrong[2];Yang, Chao[1];Shi, Ling[3]

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

年份：2019

卷号：102

起止页码：34

外文期刊名：AUTOMATICA

收录：;EI(收录号：20190406402819);WOS:【SCI-EXPANDED(收录号:WOS:000461725600005)】；

基金：This work was supported in part by the National Natural Science Foundation of China under Grant 61573143, the Hong Kong RGC General Research Fund under Grants CityU11200317 and 16208517, the Natural Science Foundation of Shanghai Under Grant 18ZR1409700, the Programme of Introducing Talents of Discipline to Universities, China (the 111 Project) under Grant B17017. The material in this paper was not presented at any conference. This paper was recommended for publication in revised form by Associate Editor Michele Basseville under the direction of Editor Torsten Soderstrom.

语种：英文

外文关键词：Distributed estimation; Modified algebraic Riccati equation; False data injection attack; Wireless sensor network

摘要：We consider the problem of network security for distributed filtering under false data injection attacks over a wireless sensor network. To resist the hostile attacks from a malicious attacker who can inject false data into communication channels according to a certain probability, we design a protector for each sensor based on the online innovation information from its neighboring sensors to decide whether to use the received data at each time. To guarantee the Gaussianity of the innovations, we use a stochastic rule to transform the threshold detection. We also provide a sufficient condition for the stability of the estimator equipped with the proposed protector under hostile attacks. Moreover, we find a critical attack probability above which the steady-state estimation error covariance will exceed a pre-set value. Finally, we compare the estimation performances among several protection strategies, and explore the relationship between the system parameters and the protection effect. (C) 2019 Elsevier Ltd. All rights reserved.