Publications by authors named "Kaijing Jin"

Article Synopsis
  • This article explores an innovative attack strategy for networked linear quadratic Gaussian systems, focusing on stealthiness defined by Kullback-Leibler divergence.
  • The attackers aim to increase costs associated with control while minimizing their own costs, addressing this challenge as a nonconvex optimization problem.
  • Through matrix decomposition, the study finds optimal strictly stealthy and ϵ-stealthy attack methods, showing improved effectiveness compared to previous suboptimal attack strategies via simulation results.
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