This paper investigates the secure state estimation problem for cyber-physical systems (CPSs) under disturbance and sparse sensor attacks.
This effect was considered clinically relevant, but considering the elevated heterogeneity (I = 58%%, p = 0.05), and limited scientific foundation (GRADE level 2, low quality of evidence) there is more research needed in order to secure the estimations.
To secure CFO estimates with high accuracy, the technique using maximum-likelihood (ML) estimation perhaps is the best choice for CFO tracking, securing fine CFO estimates.
Thus, an alternative approach was suggested to secure reliability of performance estimation from the basic measurement.
Therefore, an accurate and timely estimation of secure ranges for dynamic interchange adjustments is necessary for microgrid operators.
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However, when under attack, the attacker will deceive the state estimation and online SSA to show secure signal instead.
On the other hand, the server is responsible for configuring these modules, performing computer vision algorithms and water balance estimation, storing all data in a secure database, and interacting with the user interface using the web.
