文献类型：期刊文献

英文题名：Event-based distributed state estimation under deception attack

作者：Yang, Wen[1];Lei, Li[1];Yang, Chao[1]

机构：[1]East China Univ Sci & Technol, Minist Educ, Key Lab Adv Control & Optimizat Chem Proc, Shanghai, Peoples R China

年份：2017

卷号：270

起止页码：145

外文期刊名：NEUROCOMPUTING

收录：;EI(收录号：20172703898552);WOS:【SCI-EXPANDED(收录号:WOS:000412618300017)】；

基金：This work was supported in part by the National Natural Science Foundation of China under Grant(61573143), the Innovation Program of Shanghai Municipal Education Commission under Grant no. 142z55

语种：英文

外文关键词：Distributed state estimation; Event-based strategy; False data injection attack

摘要：Recently, security issues in wireless sensor networks (WSNs) have attracted lots of attention. It is necessary to design effective measures against the attacker. In this paper, a novel distributed state estimator with an event-triggered scheme is proposed to defend against false data injection attack in WSNs. Here, each sensor detects the rightness of its estimate according to a condition at each time step. When the condition is satisfied, the sensor regards it is not attacked, then it is triggered to send the estimate to its neighboring sensors; Otherwise, the sensor is not triggered. Based on the event-triggered scheme, an optimal estimator gain is designed by minimizing the mean-squared estimation error covariance, and then a sufficient condition is provided to guarantee the stability of the proposed distributed estimator. Finally, a numerical example is provided to illustrate the effectiveness of the proposed estimator with event-based strategy. (C) 2017 Elsevier B.V. All rights reserved.