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    Researchers developed optimal stealthy attack strategies for cyber-physical systems (CPSs). The study introduces novel models for strictly stealthy and epsilon-stealthy attacks, balancing performance and undetectability in LQG systems.

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    Area of Science:

    • Cyber-physical Systems Security
    • Control Theory
    • Optimization

    Background:

    • Cyber-physical systems (CPSs) are increasingly vulnerable to sophisticated attacks.
    • Stealthy attacks aim to maximize system disruption while evading detection.
    • Linear Quadratic Gaussian (LQG) dynamics are a common model for CPSs.

    Purpose of the Study:

    • To design optimal stealthy attack strategies for LQG-based CPSs.
    • To develop a novel attack model allowing for strictly stealthy and epsilon-stealthy attacks.
    • To analyze the trade-off between attack performance and stealthiness.

    Main Methods:

    • Development of a novel attack model for CPSs.
    • Utilizing semidefinite programming for strictly stealthy attacks.
    • Employing convex optimization for epsilon-stealthy attacks.

    Main Results:

    • Strictly stealthy attacks offer optimal but limited performance.
    • Epsilon-stealthy attacks achieve higher performance by sacrificing some stealthiness.
    • An optimal epsilon-stealthy attack strategy was designed, outperforming existing suboptimal methods.

    Conclusions:

    • The proposed methods effectively balance attack performance and stealthiness in CPSs.
    • The study provides a framework for designing advanced cyber attacks on LQG systems.
    • Simulations validate the effectiveness of the developed stealthy attack strategies.