Identification of FIR Systems With Binary-Valued Observations Against Data Tampering Attacks
Jin Guo, Ruizhe Jia, Ruinan Su, Yanlong Zhao
Abstract
This article addresses the security issue against data tampering attacks in the identification of finite impulse response (FIR) systems with binary-valued observations. First, the data tampering rate and estimation error caused by the network attack are derived. From the perspective of the attacker, it is investigated how to achieve the maximum attack effect with the minimum energy. Second, the compensation-type defense scheme is designed. Under this, the identification algorithm is constructed, and its strong convergence is proved. Taking the covariance matrix of the estimation error as the performance index, the optimal defense scheme is given. Finally, the results obtained are verified by simulation example.