Adaptive state estimation for cyber physical systems under sparse attacks

2018 ◽  
Vol 41 (6) ◽  
pp. 1571-1579 ◽  
Author(s):  
Hao Zhang ◽  
Chen Peng ◽  
Hongtao Sun ◽  
Dajun Du
Keyword(s):  
State Estimation ◽  
Adaptive Estimation ◽  
Computing Time ◽  
Estimation Method ◽  
Cyber Physical Systems ◽  
Estimation Problem ◽  
Step Size ◽  
Estimation Errors ◽  
Physical Systems ◽  
Dynamic Estimation

This paper investigates the state estimation problem for cyber physical systems under sparse attacks. Firstly, the fundamental state estimation problem is transferred to an optimization problem with a unique solution. Secondly, an adaptive estimation method for sparse attacks is proposed, which convergence property is well proved. The advantage of proposed method is that the step-size can be adaptively adjusted based on the dynamic estimation errors. Therefore, the computing time is less than some existing methods while guaranteeing the desired performance. Then, a suitable state feedback is designed to improve the computing speed while enhancing the resiliency for the destroyed system. Finally, the speed performance and accuracy of proposed algorithm are verified by two numerical examples.

Sensor and Actuator Intrusion Detection for Cyber-Physical Systems via Adaptive Estimation Algorithm

2020 ◽  
Author(s):  
Jiayi Su ◽  
Yuqin Weng ◽  
Susan C. Schneider ◽  
Edwin E. Yaz
Keyword(s):  
Kalman Filters ◽  
Adaptive Estimation ◽  
Estimation Algorithm ◽  
Cyber Physical Systems ◽  
Motor Speed ◽  
New Approach ◽  
Physical Systems ◽  
Unknown Type ◽  
Different Types ◽  
Conditional State

Abstract In this work, a new approach to detect sensor and actuator intrusion for Cyber-Physical Systems using a bank of Kalman filters is presented. The case where the unknown type of the intrusion signal is considered first, using two Kalman filters in a bank to provide the conditional state estimates, then the unknown type of intrusion signal can be detected properly via the adaptive estimation algorithm. The case where the target (either sensor or actuator) of the intrusion signal is unknown is also considered, using four Kalman filters in a bank designed to detect if the intrusion signal is about to affect healthy sensor or actuator signal. To test these methods, a DC motor speed control system subject to attack by different types of sensor and actuator signals is simulated. Simulations show that different types of sensor and actuator intrusion signals can be detected properly without the knowledge of the nature and the type of these signals.

scholarly journals Joint attack detection and secure state estimation of cyber‐physical systems

2019 ◽  
Vol 30 (11) ◽  
pp. 4303-4330 ◽  
Author(s):  
Nicola Forti ◽  
Giorgio Battistelli ◽  
Luigi Chisci ◽  
Bruno Sinopoli
Keyword(s):  
State Estimation ◽  
Cyber Physical Systems ◽  
Attack Detection ◽  
Physical Systems

scholarly journals State Estimation and Event-Triggered Control for Cyber-Physical Systems under Malicious Attack

2019 ◽  
Vol 2019 ◽  
pp. 1-10
Author(s):  
Yongzhen Guo ◽  
Baijing Han ◽  
Weiping Wang ◽  
Manman Yuan
Keyword(s):  
State Estimation ◽  
Finite Time ◽  
Cyber Physical Systems ◽  
The State ◽  
State Information ◽  
Physical Systems ◽  
Malicious Attack ◽  
Event Triggered

This paper is concerned with the security state estimation and event-triggered control of cyber-physical systems (CPSs) under malicious attack. Aiming at this problem, a finite-time observer is designed to estimate the state of the system successfully. Then, according to the state information, the event-triggered controller is designed through the event-triggered communication. It is proved that the system is uniformly and finally bounded. Finally, the effectiveness of the proposed method is verified by a simulation example.

scholarly journals Exploring Risks Transferred from Cloud-Based Information Systems: A Quantitative and Longitudinal Model

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3488 ◽  
Author(s):  
Wafa Bouaynaya ◽  
Hongbo Lyu ◽  
Zuopeng Zhang
Keyword(s):  
Cloud Computing ◽  
Information System ◽  
Information Systems ◽  
Internet Of Things ◽  
Risk Estimation ◽  
Estimation Method ◽  
Cyber Physical Systems ◽  
Longitudinal Model ◽  
Physical Systems ◽  
A Company

With the growing popularity of Internet of Things (IoT) and Cyber-Physical Systems (CPS), cloud- based systems have assumed a greater important role. However, there lacks formal approaches to modeling the risks transferred through information systems implemented in a cloud-based environment. This paper explores formal methods to quantify the risks associated with an information system and evaluate its variation throughout its implementation. Specifically, we study the risk variation through a quantitative and longitudinal model spanning from the launch of a cloud-based information systems project to its completion. In addition, we propose to redefine the risk estimation method to differentiate a mitigated risk from an unmitigated risk. This research makes valuable contributions by helping practitioners understand whether cloud computing presents a competitive advantage or a threat to the sustainability of a company.

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