Abstract
Cyber-physical systems (CPSs) have been applied to water distribution systems for the efficient system operation and maintenance as an application field of fourth industrial revolution. Although CPSs technology is an efficient technology based on information communication technology, it is vulnerable to cyber-attack due to information disturbance of sensor and communication server. These cyber-attack causes serious problems in the operation of the water distribution systems such as decreases of water supply, water pollution and damage to physical systems. Therefore, a few studies were performed to organize the various cyber-attack scenarios and cyber-attack detection algorithms were developed. In this study, an artificial neural network model is applied for the detection of cyber-attack by varying the number of neurons. The developed detection technique can be contributed to the establishment of reliable the water distribution systems in real operation.
Original language | English |
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Title of host publication | Advances in Harmony Search, Soft Computing and Applications, ICHSA 2019 |
Editors | Joong Hoon Kim, Zong Woo Geem, Donghwi Jung, Do Guen Yoo, Anupam Yadav |
Publisher | Springer |
Pages | 82-88 |
Number of pages | 7 |
ISBN (Print) | 9783030319663 |
DOIs | |
Publication status | Published - 2020 |
Event | 5th International Conference on Harmony Search, Soft Computing and Applications, ICHSA 2019 - Kunming, China Duration: 2019 Jul 20 → 2019 Jul 22 |
Publication series
Name | Advances in Intelligent Systems and Computing |
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Volume | 1063 |
ISSN (Print) | 2194-5357 |
ISSN (Electronic) | 2194-5365 |
Conference
Conference | 5th International Conference on Harmony Search, Soft Computing and Applications, ICHSA 2019 |
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Country/Territory | China |
City | Kunming |
Period | 19/7/20 → 19/7/22 |
Bibliographical note
Funding Information:Acknowledgements. This work was supported by a grant from The National Research Foundation (NRF) of Korea, funded by the Korean government (MSIP) (No. 2016R1A2A1A 05005306).
Funding Information:
This work was supported by a grant from The National Research Foundation (NRF) of Korea, funded by the Korean government (MSIP) (No. 2016R1A2A1A 05005306).
Publisher Copyright:
© 2020, Springer Nature Switzerland AG.
Keywords
- Artificial neural network
- Cyber-attack detection
- Neurons
- Optimization
ASJC Scopus subject areas
- Control and Systems Engineering
- Computer Science(all)