A tractable framework for optimal stealthy attacks in partially observed linear systems via innovation likelihood detection, with hierarchical optimization and separation principle yielding semi-explicit adaptive attacks.
Integrating sequential hypothesis testing into adversarial 12 games: A Sun Zi-inspired framework
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Optimal Design of Stealthy Attacks in Partially Observed Linear Systems: A Likelihood-Based Approach
A tractable framework for optimal stealthy attacks in partially observed linear systems via innovation likelihood detection, with hierarchical optimization and separation principle yielding semi-explicit adaptive attacks.