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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