Identification of Interdependencies and Prediction of Fault Propagation for Cyber-physical Systems
Interdependence is an intrinsic feature of cyber-physical systems. Cyber and physical components are tightly integrated with each other, and hence, a trivial impairment in a part of the system may affect several components, leading to a sequence of failures that collapses the entire system. In this paper, we seek to identify the interdependencies among the components of a cyber-physical system using correlation metrics as well as a heuristic causation analysis method. We also demonstrate applicability of neural networks for prediction of imminent failures given the current system state. The proposed prediction tool can help system operators to perform timely preventive actions and mitigate the consequences of accidental failures and malicious attacks. As a case study, we have analyzed two smart grid test cases based on IEEE power bus systems, namely, IEEE-14 and IEEE-57.
K. Marashi et al., "Identification of Interdependencies and Prediction of Fault Propagation for Cyber-physical Systems," Reliability Engineering and System Safety, vol. 215, article no. 107787, Elsevier, Nov 2021.
The definitive version is available at https://doi.org/10.1016/j.ress.2021.107787
Electrical and Computer Engineering
Intelligent Systems Center
Keywords and Phrases
Correlation And Causation; Cyber-physical Systems; Failure Prediction; Fault Propagation; Interdependency; Neural Networks; Smart Grid
International Standard Serial Number (ISSN)
Article - Journal
© 2021 Elsevier, All rights reserved.
01 Nov 2021