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False data injection attack on consensus‐based distributed estimation
Author(s) -
Lei L.,
Yang W.,
Yang C.,
Shi H. B.
Publication year - 2016
Publication title -
international journal of robust and nonlinear control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.361
H-Index - 106
eISSN - 1099-1239
pISSN - 1049-8923
DOI - 10.1002/rnc.3645
Subject(s) - estimator , computer science , estimation , set (abstract data type) , mean squared error , wireless sensor network , stability (learning theory) , mathematical optimization , mathematics , computer network , engineering , statistics , machine learning , systems engineering , programming language
Summary We consider security issues for consensus‐based distributed estimation problem. In a sensor network, an attacker with limited power injects random false data into the communication links so as to degrade the network performance. First, an optimal estimator is designed by minimizing the mean‐squared estimation error of each sensor under hostile attacks. Then, a sufficient condition is provided to guarantee the stability of the proposed estimator. Finally, a set of suboptimal attacking sequences is obtained for the attacker to maximize the network estimation error. Illustrative examples are provided to verify the effectiveness of the suboptimal attacking strategy. Copyright © 2016 John Wiley & Sons, Ltd.