期刊
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
卷 51, 期 12, 页码 7622-7632出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSMC.2020.2981478
关键词
Signal to noise ratio; Interference; Denial-of-service attack; Optimization; Mathematical model; Dynamic scheduling; State estimation; Cyber-physical systems (CPSs); denial-of-service (DoS) attack; Markov decision problem (MDP); remote state estimation (RSE); value iteration adaptive dynamic programming (ADP)
资金
- National Natural Science Foundation of China [61573036, 61174057]
This article discusses the energy-limited denial-of-service attack scheduling problem in remote state estimation under signal-to-interference-plus-noise ratio-based channels. It presents a mathematical model and algorithm to address the optimization problem, and demonstrates the effectiveness and feasibility of the method through simulation results.
This article considers the energy-limited denial-of-service attack scheduling problem on remote state estimation under signal-to-interference-plus-noise ratio-based channels. The goal of the attacker is to design the optimal attack strategy to degrade the control performance of cyber-physical systems and to reduce his energy consumption. First, to weigh the importance between the current and future rewards, an optimization problem with a discount factor is formulated, which is used to reflect the attacker's goal. Next, a Markov decision problem (MDP) is formulated to solve the optimization problem. Due to the difficulty of solving the high-dimensional MDP with unknown transition and reward functions, a value iteration adaptive dynamic programming method is proposed to achieve an approximate optimal solution. Also, convergence analysis of the proposed algorithm is carried out. Finally, simulation results are presented to show the efficiency and feasibility of the obtained results.
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