An optimal hybrid cascade regional convolutional network for cyberattack detection.
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| Title: | An optimal hybrid cascade regional convolutional network for cyberattack detection. |
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| Authors: | Alqahtani, Ali1, Khan, Surbhi Bhatia2,3, surbhibhatia1988@yahoo.com |
| Source: | International Journal of Network Management; Sep/Oct2024, Vol. 34 Issue 5, p1-17, 17p |
| Database: | Applied Science & Technology Source |
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| FullText | Links: – Type: pdflink Text: Availability: 1 |
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| Header | DbId: aci DbLabel: Applied Science & Technology Source An: 180923705 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=180923705 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1002/nem.2247 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 17 StartPage: 1 Titles: – TitleFull: An optimal hybrid cascade regional convolutional network for cyberattack detection. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Alqahtani, Ali – PersonEntity: Name: NameFull: Khan, Surbhi Bhatia IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 09 Text: Sep/Oct2024 Type: published Y: 2024 Identifiers: – Type: issn-print Value: 10557148 Numbering: – Type: volume Value: 34 – Type: issue Value: 5 Titles: – TitleFull: International Journal of Network Management Type: main |
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