Quantum-resistant hybrid encryption framework for secure and intelligent Vehicle-to-Vehicle communication using deep representation learning models.

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Bibliographic Details
Title: Quantum-resistant hybrid encryption framework for secure and intelligent Vehicle-to-Vehicle communication using deep representation learning models.
Authors: Hasanin T; Department of Information Systems, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia., Alharbi ZH; Department of Management Information Systems, College of Business Administration, King Saud University, Riyadh, Saudi Arabia., Eltahir MM; Department of Information Systems, Applied College at Mahayil, King Khalid University, Abha, Saudi Arabia., Marzouk R; Department of Information Systems, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia., Alsirhani KF; Department of Electrical Engineering, College of Engineering, Jouf University, Sakakah, Aljouf, Kingdom of Saudi Arabia., Alsafari S; Department of Computer Science and Artificial Intelligence, College of Computer Science and Engineering, University of Jeddah, 23890, Jeddah, Saudi Arabia., Althobaiti T; Department of Computer Science, Faculty of Science, Northern Border University, 73222, Arar, Saudi Arabia., Almutairi S; Department of Computer Science, Applied College, Shaqra University, 15526, Shaqra, Saudi Arabia. sultan@su.edu.sa.
Source: Scientific reports [Sci Rep] 2026 May 07; Vol. 16 (1). Date of Electronic Publication: 2026 May 07.
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
Description
ISSN:2045-2322
DOI:10.1038/s41598-026-37282-8