In this paper,the authors consider how to design defensive countermeasures against DoS attacks for remote state estimation of multiprocess systems.For each system,a sensor will measure its state and transmits the data...In this paper,the authors consider how to design defensive countermeasures against DoS attacks for remote state estimation of multiprocess systems.For each system,a sensor will measure its state and transmits the data packets through an unreliable channel which is vulnerable to be jammed by an attacker.Under limited communication bandwidth,only a subset of sensors are allowed for data transmission,and how to select the optimal one to maximize the accuracy of remote state estimation is the focus of the proposed work.The authors first formulate this problem as a Markov decision process and investigate the existence of optimal policy.Moreover,the authors demonstrate the piecewise monotonicity structure of optimal policy.Given the difficulty of obtaining an optimal policy of large-scale problems,the authors develop a suboptimal heuristic policy based on the aforementioned policy structure and Whittle’s index.Moreover,a closed form of the indices is derived in order to reduce implementation complexity of proposed scheduling policy and numerical examples are provided to illustrate the proposed developed results.展开更多
基金supported by the National Natural Science Foundation of China under Grant No.20231120102304001,STIC under Grant Nos.62303212 and ZDSYS20220330161800001.
文摘In this paper,the authors consider how to design defensive countermeasures against DoS attacks for remote state estimation of multiprocess systems.For each system,a sensor will measure its state and transmits the data packets through an unreliable channel which is vulnerable to be jammed by an attacker.Under limited communication bandwidth,only a subset of sensors are allowed for data transmission,and how to select the optimal one to maximize the accuracy of remote state estimation is the focus of the proposed work.The authors first formulate this problem as a Markov decision process and investigate the existence of optimal policy.Moreover,the authors demonstrate the piecewise monotonicity structure of optimal policy.Given the difficulty of obtaining an optimal policy of large-scale problems,the authors develop a suboptimal heuristic policy based on the aforementioned policy structure and Whittle’s index.Moreover,a closed form of the indices is derived in order to reduce implementation complexity of proposed scheduling policy and numerical examples are provided to illustrate the proposed developed results.
