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Side Information Incorporated ϵ -Stealthy Attack Against Remote State Estimation.

Li-Wei Mao, Guang-Hong Yang

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    |May 9, 2025
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    Summary
    This summary is machine-generated.

    This study introduces a novel stealthy attack on remote state estimation in cyber-physical systems. The attack effectively maximizes estimation errors using combined intercepted and side information, outperforming existing methods.

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    Area of Science:

    • Cyber-Physical Systems
    • Control Theory
    • Network Security

    Background:

    • Remote state estimation is crucial for cyber-physical systems.
    • Stealthy attacks pose a significant threat to system integrity.
    • Existing attacks have limitations in performance and complexity.

    Purpose of the Study:

    • To design an ϵ-stealthy attack against remote state estimation.
    • To exploit both intercepted and side information for enhanced attack capabilities.
    • To maximize the attacked error covariance of the remote estimator.

    Main Methods:

    • A novel attack model based on corrupted innovation is proposed.
    • The attacked error covariance of the remote estimator is derived.
    • An analytical attack strategy is developed to maximize the error covariance.

    Main Results:

    • The proposed attack model effectively combines intercepted and side information.
    • An analytical strategy is provided to maximize the attacked error covariance.
    • The new attack demonstrates significantly improved performance compared to existing methods, using only one auxiliary filter.

    Conclusions:

    • The developed ϵ-stealthy attack is effective in degrading remote state estimation.
    • The attack strategy offers superior performance with reduced complexity.
    • Numerical simulations confirm the effectiveness and practical viability of the proposed attack.