The ability to detect the linear attack of WL-CUSUM and FMA algorithms

Duc Duong Nguyen, Minh Thuy Le, Thanh Long Cung


The problem of detecting linear attacks on industrial systems is presented in this paper. The object is attacked by linear attack is the wireless communication process from sensors to controller with simulated mathematical model (stochastic dynamical systems and random noises). The attack matrices are calculated to ensure that Kullback-Leiber (K-L) algorithm is passed. With these matrices, the window limited cumulative SUM (WL-CUSUM) algorithm and finite moving average (FMA) algorithm are utilized to detect the changes in the sequence of residuals generated from Kalman filter method and are appreciated the ability to detect the linear attack. The simulated results show that an appropriate range of threshold of the WL-CUSUM and FMA algorithm can be chosen to detect the linear attack in case the K-L method cannot detect. Moreover, tested results using the Monte Carlo simulation also show that the evaluation performance of the FMA detection algorithm is better than that of WL-CUSUM, CUSUM, and Chi-squared (Chi2).


Finite moving average; Kullback-Leiber; Linear attack; Weighted likelihood ratio; WL-CUSUM

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