Application of Artificial Neural Network for Cyber-Attack Detection in Water Distribution Systems as Cyber Physical Systems

Kyoung Won Min, Young Hwan Choi, Abobakr Khalil Al-Shamiri, Joong Hoon Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

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 languageEnglish
Title of host publicationAdvances in Harmony Search, Soft Computing and Applications, ICHSA 2019
EditorsJoong Hoon Kim, Zong Woo Geem, Donghwi Jung, Do Guen Yoo, Anupam Yadav
PublisherSpringer
Pages82-88
Number of pages7
ISBN (Print)9783030319663
DOIs
Publication statusPublished - 2020
Event5th International Conference on Harmony Search, Soft Computing and Applications, ICHSA 2019 - Kunming, China
Duration: 2019 Jul 202019 Jul 22

Publication series

NameAdvances in Intelligent Systems and Computing
Volume1063
ISSN (Print)2194-5357
ISSN (Electronic)2194-5365

Conference

Conference5th International Conference on Harmony Search, Soft Computing and Applications, ICHSA 2019
Country/TerritoryChina
CityKunming
Period19/7/2019/7/22

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)

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