Security Control of Cyber-Physical System Based on Switching Approach for Nonperiodic DoS Attacks

Author(s):  
Dong Yue ◽  
Songlin Hu ◽  
Zihao Cheng
2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Zhiwen Wang ◽  
Xiaoping Wang ◽  
Hongtao Sun ◽  
Peng Xin

This paper addresses the static output feedback predictive (SOFP) control problem with cyber-physical system (CPS) subject to Denial-of-Service (DoS) attacks. The effects of DoS attacks are reasonably assumed to the bounded consecutive packet dropouts by considering the energy constraints of an attacker. Then, a novel predictive control sequence, in which only the latest successfully received output is employed, is designed to compensate such packet dropouts caused by DoS attacks. Furthermore, the stability criterion and predictive control design are carefully derived by using the switching Lyapunov functional approach and linear matrix inequality. Compared with the previous works, the proposed predictive control strategy can compensate arbitrary packet dropouts under DoS attacks while only the latest successfully received output is available. At last, a simulation example illustrates the effectiveness of the SOFP control strategy.


Author(s):  
Vo Que Son ◽  
Do Tan A

Sensing, distributed computation and wireless communication are the essential building components of a Cyber-Physical System (CPS). Having many advantages such as mobility, low power, multi-hop routing, low latency, self-administration, utonomous data acquisition, and fault tolerance, Wireless Sensor Networks (WSNs) have gone beyond the scope of monitoring the environment and can be a way to support CPS. This paper presents the design, deployment, and empirical study of an eHealth system, which can remotely monitor vital signs from patients such as body temperature, blood pressure, SPO2, and heart rate. The primary contribution of this paper is the measurements of the proposed eHealth device that assesses the feasibility of WSNs for patient monitoring in hospitals in two aspects of communication and clinical sensing. Moreover, both simulation and experiment are used to investigate the performance of the design in many aspects such as networking reliability, sensing reliability, or end-to-end delay. The results show that the network achieved high reliability - nearly 97% while the sensing reliability of the vital signs can be obtained at approximately 98%. This indicates the feasibility and promise of using WSNs for continuous patient monitoring and clinical worsening detection in general hospital units.


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