An Optimized Multiclass Machine Learning Approach for Detecting Advanced Intrusions in IoT Systems.
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| Title: | An Optimized Multiclass Machine Learning Approach for Detecting Advanced Intrusions in IoT Systems. |
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| Authors: | Labib, Mostafa Ibrahim1, mostafa.elkhalil@fa-hists.edu.eg, Mohamed, Mohamed Salah2, mohamed.smah@fci.suezuni.edu.eg, El-Desokey, Amira Ibrahim3, amira.eldesouky@fa-hists.edu.eg, Mohamed, Fatma Harby1,4, fatma.mohamed@fa-hists.edu.eg |
| Source: | Engineering, Technology & Applied Science Research; Feb2026, Vol. 16 Issue 1, p32564-32569, 6p |
| 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: 192212735 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=192212735 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.48084/etasr.15800 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 6 StartPage: 32564 Titles: – TitleFull: An Optimized Multiclass Machine Learning Approach for Detecting Advanced Intrusions in IoT Systems. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Labib, Mostafa Ibrahim – PersonEntity: Name: NameFull: Mohamed, Mohamed Salah – PersonEntity: Name: NameFull: El-Desokey, Amira Ibrahim – PersonEntity: Name: NameFull: Mohamed, Fatma Harby IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 02 Text: Feb2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 22414487 Numbering: – Type: volume Value: 16 – Type: issue Value: 1 Titles: – TitleFull: Engineering, Technology & Applied Science Research Type: main |
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