Enhancing Security in Wireless Sensor Networks: A Machine Learning-based DoS Attack Detection.
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| Title: | Enhancing Security in Wireless Sensor Networks: A Machine Learning-based DoS Attack Detection. |
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| Authors: | Al Sukkar, Ghadeer1,2, gdy9224472@ju.edu.jo, Al-Sharaeh, Saleh1, ssharaeh@ju.edu.jo |
| Source: | Engineering, Technology & Applied Science Research; Feb2025, Vol. 15 Issue 1, p19712-19719, 8p |
| Database: | Applied Science & Technology Source |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: aci DbLabel: Applied Science & Technology Source An: 183221439 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Enhancing Security in Wireless Sensor Networks: A Machine Learning-based DoS Attack Detection. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AU" term="%22Al+Sukkar%2C+Ghadeer%22">Al Sukkar, Ghadeer</searchLink><relatesTo>1,2</relatesTo>, <i>gdy9224472@ju.edu.jo</i><br /><searchLink fieldCode="AU" term="%22Al-Sharaeh%2C+Saleh%22">Al-Sharaeh, Saleh</searchLink><relatesTo>1</relatesTo>, <i>ssharaeh@ju.edu.jo</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Engineering%2C+Technology+%26+Applied+Science+Research%22">Engineering, Technology & Applied Science Research</searchLink>; Feb2025, Vol. 15 Issue 1, p19712-19719, 8p |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=183221439 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.48084/etasr.7191 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 8 StartPage: 19712 Titles: – TitleFull: Enhancing Security in Wireless Sensor Networks: A Machine Learning-based DoS Attack Detection. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Al Sukkar, Ghadeer – PersonEntity: Name: NameFull: Al-Sharaeh, Saleh IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 02 Text: Feb2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 22414487 Numbering: – Type: volume Value: 15 – Type: issue Value: 1 Titles: – TitleFull: Engineering, Technology & Applied Science Research Type: main |
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