Advancements in cyberthreat intelligence through resource exhaustion attack detection using hybrid deep learning with heuristic search algorithms.
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| Title: | Advancements in cyberthreat intelligence through resource exhaustion attack detection using hybrid deep learning with heuristic search algorithms. |
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| Authors: | Jayanthi S; Department of Artificial Intelligence & Data Science, Faculty of Science and Technology (IcfaiTech), The ICFAI Foundation for Higher Education (IFHE), Hyderabad, Telangana, 501503, India., Bavirthi SS; Department of Information Technology, Chaitanya Bharathi Institute of Technology, Gandipet, Hyderabad, 500075, India., Murali P; CSE Department, Aditya University, Surampalem, Andhra Pradesh, India., Kumar KV; Department of CSE, GITAM School of Technology, GITAM University, Visakhapatnam, India., Alkahtani HK; Department of Information Systems, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, Riyadh, 11671, Saudi Arabia. Hkalqahtani@pnu.edu.sa., Ishak MK; Department of Electrical and Computer Engineering, College of Engineering and Information Technology, Ajman University, Ajman, United Arab Emirates., Mostafa SM; Computer Science Department, Faculty of Computers and Information, South Valley University, Qena, 83523, Egypt. |
| Source: | Scientific reports [Sci Rep] 2025 Aug 19; Vol. 15 (1), pp. 30461. Date of Electronic Publication: 2025 Aug 19. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: MEDLINE; PubMed not MEDLINE |
| Database: | MEDLINE Ultimate |
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| Header | DbId: mdl DbLabel: MEDLINE Ultimate An: 40830149 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Advancements in cyberthreat intelligence through resource exhaustion attack detection using hybrid deep learning with heuristic search algorithms. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AU" term="%22Jayanthi+S%22">Jayanthi S</searchLink>; Department of Artificial Intelligence & Data Science, Faculty of Science and Technology (IcfaiTech), The ICFAI Foundation for Higher Education (IFHE), Hyderabad, Telangana, 501503, India.<br /><searchLink fieldCode="AU" term="%22Bavirthi+SS%22">Bavirthi SS</searchLink>; Department of Information Technology, Chaitanya Bharathi Institute of Technology, Gandipet, Hyderabad, 500075, India.<br /><searchLink fieldCode="AU" term="%22Murali+P%22">Murali P</searchLink>; CSE Department, Aditya University, Surampalem, Andhra Pradesh, India.<br /><searchLink fieldCode="AU" term="%22Kumar+KV%22">Kumar KV</searchLink>; Department of CSE, GITAM School of Technology, GITAM University, Visakhapatnam, India.<br /><searchLink fieldCode="AU" term="%22Alkahtani+HK%22">Alkahtani HK</searchLink>; Department of Information Systems, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, Riyadh, 11671, Saudi Arabia. Hkalqahtani@pnu.edu.sa.<br /><searchLink fieldCode="AU" term="%22Ishak+MK%22">Ishak MK</searchLink>; Department of Electrical and Computer Engineering, College of Engineering and Information Technology, Ajman University, Ajman, United Arab Emirates.<br /><searchLink fieldCode="AU" term="%22Mostafa+SM%22">Mostafa SM</searchLink>; Computer Science Department, Faculty of Computers and Information, South Valley University, Qena, 83523, Egypt. – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22101563288%22">Scientific reports</searchLink> [Sci Rep] 2025 Aug 19; Vol. 15 (1), pp. 30461. <i>Date of Electronic Publication: </i>2025 Aug 19. – Name: TypePub Label: Publication Type Group: TypPub Data: Journal Article – Name: TitleSource Label: Journal Info Group: Src Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Nature+Publishing+Group%22">Nature Publishing Group </searchLink><i>Country of Publication: </i>England <i>NLM ID: </i>101563288 <i>Publication Model: </i>Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>2045-2322 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2220452322%22">20452322 </searchLink><i>NLM ISO Abbreviation: </i>Sci Rep <i>Subsets: </i>MEDLINE; PubMed not MEDLINE |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdl&AN=40830149 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1038/s41598-025-13305-8 Languages: – Code: eng Text: English PhysicalDescription: Pagination: StartPage: 30461 Titles: – TitleFull: Advancements in cyberthreat intelligence through resource exhaustion attack detection using hybrid deep learning with heuristic search algorithms. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Jayanthi S – PersonEntity: Name: NameFull: Bavirthi SS – PersonEntity: Name: NameFull: Murali P – PersonEntity: Name: NameFull: Kumar KV – PersonEntity: Name: NameFull: Alkahtani HK – PersonEntity: Name: NameFull: Ishak MK – PersonEntity: Name: NameFull: Mostafa SM IsPartOfRelationships: – BibEntity: Dates: – D: 19 M: 08 Text: 2025 Aug 19 Type: published Y: 2025 Identifiers: – Type: issn-electronic Value: 2045-2322 Numbering: – Type: volume Value: 15 – Type: issue Value: 1 Titles: – TitleFull: Scientific reports Type: main |
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