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. |
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| 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] |
| Copyright of International Transactions on Electrical Energy Systems is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
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| Header | DbId: 8gh DbLabel: GreenFILE An: 159135575 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Integrating Industrial Appliances for Security Enhancement in Data Point Using SCADA Networks with Learning Algorithm. – Name: Author Label: Authors Group: Au 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) – Name: TitleSource Label: Source Group: Src 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. – Name: Subject Label: Subject Terms Group: Su 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] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of International Transactions on Electrical Energy Systems is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1155/2022/8685235 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 11 StartPage: 1 Subjects: – SubjectFull: Machine learning Type: general – SubjectFull: Industrial security Type: general – SubjectFull: End-to-end delay Type: general – SubjectFull: Data security Type: general – SubjectFull: Supervisory control systems Type: general Titles: – TitleFull: Integrating Industrial Appliances for Security Enhancement in Data Point Using SCADA Networks with Learning Algorithm. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Khadidos, Alaa O. – PersonEntity: Name: NameFull: Khadidos, Adil O. – PersonEntity: Name: NameFull: Manoharan, Hariprasath – PersonEntity: Name: NameFull: Alyoubi, Khaled H. – PersonEntity: Name: NameFull: Alshareef, Abdulrhman M. – PersonEntity: Name: NameFull: Selvarajan, Shitharth IsPartOfRelationships: – BibEntity: Dates: – D: 15 M: 09 Text: 9/15/2022 Type: published Y: 2022 Identifiers: – Type: issn-print Value: 20507038 Titles: – TitleFull: International Transactions on Electrical Energy Systems Type: main |
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