A Novel Method to Prevent Misconfigurations of Industrial Automation and Control Systems
| Autor: | Yani Ge, Yongzheng Zhang, Peiran Yu, Yu Zhang, Thar Baker, Jianzhong Zhang |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
QA75
Correctness business.industry Computer science Distributed computing 020208 electrical & electronic engineering Hash function 02 engineering and technology Automation QA76 Computer Science Applications Data modeling Control and Systems Engineering Control system 0202 electrical engineering electronic engineering information engineering Electrical and Electronic Engineering business Information Systems |
| Zdroj: | IEEE Transactions on Industrial Informatics. 17:4210-4218 |
| ISSN: | 1941-0050 1551-3203 |
| DOI: | 10.1109/tii.2020.3017754 |
| Popis: | Configuration errors are among the dominant causes of system faults for the industrial automation and control systems (IACS). It is difficult to detect and correct such errors of IACS as there are various kinds of systems and devices with miscellaneous configuration specifications. In this paper, we first propose a streaming algorithm to keep all the configuration changes in the limited memory space. And, when making a new configuration change, another novel streaming algorithm is proposed to search and return all the similar historical changes which can be used to validate this new one. So far, we are the first to model the configuration changes of IACS as a data stream and apply the streaming similarity search in correcting configuration errors while overcoming the inherent unbounded-memory bottleneck. The theoretical correctness and complexity analyses are presented. Experiments with real and synthetic datasets confirm the theoretical analyses and demonstrate the effectiveness of the proposed method in preventing misconfigurations of IACS. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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