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Integrating Industrial Appliances for Security Enhancement in Data Point Using SCADA Networks with Learning Algorithm.

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Title: Integrating Industrial Appliances for Security Enhancement in Data Point Using SCADA Networks with Learning Algorithm.
Authors: Khadidos, Alaa O.1 (AUTHOR), Khadidos, Adil O.2 (AUTHOR), Manoharan, Hariprasath3 (AUTHOR), Alyoubi, Khaled H.1 (AUTHOR), Alshareef, Abdulrhman M.1 (AUTHOR), Selvarajan, Shitharth4 (AUTHOR)
Source: International Transactions on Electrical Energy Systems. 9/15/2022, p1-11. 11p.
Subject Terms: *Machine learning, *Industrial security, *End-to-end delay, *Data security, *Supervisory control systems
Abstract: The process of ensuring automatic operation for industrial appliances using both supervision and control techniques is a challenging task. Therefore, this article focuses on implementing Supervisory Control and Data Acquisition (SCADA) for controlling all industrial appliances. The design process of implementation case is performed using an analytical framework by examining the primary energy sources at the initial state; thus, a smart network is supported. The designed mathematical model is integrated with a learning technique that allocates resources at proper quantities. Further, the complex manual tuning of individual appliances is avoided in the projected method as the input variables are driven in a direct way at reduced loss state. In addition, the data processing state of individual appliances is carried out using central data controller where all parametric values are stored. In case any errors are observed, then SCADA network fixes the error in an automated way, reducing end-to-end delays in all appliances. To validate the effectiveness of the proposed method, five scenarios are examined and simulated where outcomes prove that SCADA network using learning models provides optimal results on an average of 84 percent as compared to the existing models without learning algorithm. [ABSTRACT FROM AUTHOR]
Database: Energy & Power Source
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DbLabel: Energy & Power Source
An: 159135575
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  Label: Title
  Group: Ti
  Data: Integrating Industrial Appliances for Security Enhancement in Data Point Using SCADA Networks with Learning Algorithm.
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  Data: <searchLink fieldCode="AR" term="%22Khadidos%2C+Alaa+O%2E%22">Khadidos, Alaa O.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Khadidos%2C+Adil+O%2E%22">Khadidos, Adil O.</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Manoharan%2C+Hariprasath%22">Manoharan, Hariprasath</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Alyoubi%2C+Khaled+H%2E%22">Alyoubi, Khaled H.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Alshareef%2C+Abdulrhman+M%2E%22">Alshareef, Abdulrhman M.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Selvarajan%2C+Shitharth%22">Selvarajan, Shitharth</searchLink><relatesTo>4</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22International+Transactions+on+Electrical+Energy+Systems%22">International Transactions on Electrical Energy Systems</searchLink>. 9/15/2022, p1-11. 11p.
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  Data: *<searchLink fieldCode="DE" term="%22Machine+learning%22">Machine learning</searchLink><br />*<searchLink fieldCode="DE" term="%22Industrial+security%22">Industrial security</searchLink><br />*<searchLink fieldCode="DE" term="%22End-to-end+delay%22">End-to-end delay</searchLink><br />*<searchLink fieldCode="DE" term="%22Data+security%22">Data security</searchLink><br />*<searchLink fieldCode="DE" term="%22Supervisory+control+systems%22">Supervisory control systems</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: The process of ensuring automatic operation for industrial appliances using both supervision and control techniques is a challenging task. Therefore, this article focuses on implementing Supervisory Control and Data Acquisition (SCADA) for controlling all industrial appliances. The design process of implementation case is performed using an analytical framework by examining the primary energy sources at the initial state; thus, a smart network is supported. The designed mathematical model is integrated with a learning technique that allocates resources at proper quantities. Further, the complex manual tuning of individual appliances is avoided in the projected method as the input variables are driven in a direct way at reduced loss state. In addition, the data processing state of individual appliances is carried out using central data controller where all parametric values are stored. In case any errors are observed, then SCADA network fixes the error in an automated way, reducing end-to-end delays in all appliances. To validate the effectiveness of the proposed method, five scenarios are examined and simulated where outcomes prove that SCADA network using learning models provides optimal results on an average of 84 percent as compared to the existing models without learning algorithm. [ABSTRACT FROM AUTHOR]
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        Value: 10.1155/2022/8685235
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      – Code: eng
        Text: English
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        PageCount: 11
        StartPage: 1
    Subjects:
      – SubjectFull: Machine learning
        Type: general
      – SubjectFull: Industrial security
        Type: general
      – SubjectFull: End-to-end delay
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      – SubjectFull: Data security
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      – SubjectFull: Supervisory control systems
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      – TitleFull: Integrating Industrial Appliances for Security Enhancement in Data Point Using SCADA Networks with Learning Algorithm.
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            NameFull: Alyoubi, Khaled H.
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            NameFull: Alshareef, Abdulrhman M.
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            NameFull: Selvarajan, Shitharth
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            – D: 15
              M: 09
              Text: 9/15/2022
              Type: published
              Y: 2022
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              Value: 20507038
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            – TitleFull: International Transactions on Electrical Energy Systems
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