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Robust Partial-Nodes-Based State Estimation for Complex Networks Under Deception Attacks.

Nan Hou, Zidong Wang, Daniel W C Ho

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    This study introduces partial-nodes-based state estimators (PNBSEs) for uncertain complex networks facing delays and random deception attacks. The method ensures estimation error meets security constraints despite disturbances and attacks.

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    Area of Science:

    • Control Systems Engineering
    • Network Security
    • Stochastic Systems

    Background:

    • Complex networks are vulnerable to cyber threats like random deception attacks (RODAs).
    • State estimation in these networks is challenging due to uncertainties, delays, and potential data loss from compromised nodes.
    • Partial measurements are often necessary in harsh environments.

    Purpose of the Study:

    • To design partial-nodes-based state estimators (PNBSEs) for uncertain complex networks.
    • To ensure the estimation error dynamics satisfy security constraints under stochastic disturbances and RODAs.
    • To develop a method for deriving estimator gains using matrix inequalities.

    Main Methods:

    • Design of PNBSEs utilizing partial network measurements.
    • Incorporation of norm-bounded uncertainties in network parameters and couplings.
    • Stochastic analysis to derive conditions for security performance.
    • Solving matrix inequalities with nonlinear constraints to obtain estimator gains.

    Main Results:

    • Sufficient conditions derived to guarantee security performance of PNBSEs.
    • Estimator gains obtained through solving matrix inequalities.
    • Method validated via simulation studies demonstrating security performance.

    Conclusions:

    • The proposed PNBSEs effectively address state estimation challenges in uncertain complex networks with delays and RODAs.
    • The derived conditions and gain calculation method ensure robust security performance.
    • The approach provides a reliable method for state estimation in cyber-physical systems.