Authentication based vanet for data transfer: unveiling the ability of deep learning models for attack classification.
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| Title: | Authentication based vanet for data transfer: unveiling the ability of deep learning models for attack classification. |
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| Authors: | Soares, Komala1, komalasoares7817@gmail.com, Shinde, Arundhati A.1 |
| Source: | Multimedia Tools & Applications; Aug2025, Vol. 84 Issue 27, p33041-33070, 30p |
| 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: 187118463 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Authentication based vanet for data transfer: unveiling the ability of deep learning models for attack classification. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AU" term="%22Soares%2C+Komala%22">Soares, Komala</searchLink><relatesTo>1</relatesTo>, <i>komalasoares7817@gmail.com</i><br /><searchLink fieldCode="AU" term="%22Shinde%2C+Arundhati+A%2E%22">Shinde, Arundhati A.</searchLink><relatesTo>1</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Multimedia+Tools+%26+Applications%22">Multimedia Tools & Applications</searchLink>; Aug2025, Vol. 84 Issue 27, p33041-33070, 30p |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=187118463 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s11042-024-20489-0 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 30 StartPage: 33041 Titles: – TitleFull: Authentication based vanet for data transfer: unveiling the ability of deep learning models for attack classification. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Soares, Komala – PersonEntity: Name: NameFull: Shinde, Arundhati A. IsPartOfRelationships: – BibEntity: Dates: – D: 21 M: 08 Text: Aug2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 13807501 Numbering: – Type: volume Value: 84 – Type: issue Value: 27 Titles: – TitleFull: Multimedia Tools & Applications Type: main |
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