A Hybrid Heuristic-Machine Learning Framework for Phishing Detection Using MultiDomain Feature Analysis.
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| Title: | A Hybrid Heuristic-Machine Learning Framework for Phishing Detection Using MultiDomain Feature Analysis. |
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| Authors: | Jadhav, Ashvini1, ashvinigjadhav@gmail.com, Chandre, Pankaj1, pankajchandre30@gmail.com |
| Source: | Engineering, Technology & Applied Science Research; Oct2025, Vol. 15 Issue 5, p27219-27226, 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: 189243371 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: A Hybrid Heuristic-Machine Learning Framework for Phishing Detection Using MultiDomain Feature Analysis. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AU" term="%22Jadhav%2C+Ashvini%22">Jadhav, Ashvini</searchLink><relatesTo>1</relatesTo>, <i>ashvinigjadhav@gmail.com</i><br /><searchLink fieldCode="AU" term="%22Chandre%2C+Pankaj%22">Chandre, Pankaj</searchLink><relatesTo>1</relatesTo>, <i>pankajchandre30@gmail.com</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>; Oct2025, Vol. 15 Issue 5, p27219-27226, 8p |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=189243371 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.48084/etasr.11548 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 8 StartPage: 27219 Titles: – TitleFull: A Hybrid Heuristic-Machine Learning Framework for Phishing Detection Using MultiDomain Feature Analysis. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Jadhav, Ashvini – PersonEntity: Name: NameFull: Chandre, Pankaj IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 10 Text: Oct2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 22414487 Numbering: – Type: volume Value: 15 – Type: issue Value: 5 Titles: – TitleFull: Engineering, Technology & Applied Science Research Type: main |
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