Secure State Estimation Against DoS Attack Over SINR-Based Channels: A Stackelberg Game Approach

• 成果类型: Article
• 署名作者: Yu, Yan; Yang, Wen; Ren, Xiaoqiang; Shi, Ling; Wang, Xiaofan
• 署名单位: East China University of Science and Technology; Shanghai University; Hong Kong University of Science & Technology; Shanghai Institute of Technology
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2025.3649275
• 发表日期: 2026
• 关键词: POWER SCHEDULE; COMMUNICATION; sensors

摘要

This article investigates defense strategies against denial-of-service (DoS) attacks in remote state estimation. When DoS attacks disrupt sensor communication, the signal-to-interference-and-noise ratio decreases, thereby reducing the probability of successful state estimate transmission to the remote estimator and ultimately degrading estimation accuracy. The interaction between the sensor and attacker is modeled as a nonzero-sum Stackelberg game, where the smart sensor first determines a communication channel, and the attacker then chooses its energy allocation. The equilibrium of the Stackelberg game is investigated in two scenarios. In the static game scenario, each player aims to maximize the one-step objective, with equilibrium strategies derived via convex optimization. In the dynamic game scenario, each player seeks to maximize the long-term accumulated reward. A reinforcement learning algorithm is proposed to attain the equilibrium, and the convergence of optimal stationary strategies is proven. In addition, structural properties of the optimal solutions are also analyzed. Finally, numerical simulations are provided to validate the feasibility and effectiveness of the proposed methods.