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A hybrid deep learning approach with temporal awareness for intelligent intrusion detection in 6G-enabled IIoT networks.

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Bibliographic Details
Title: A hybrid deep learning approach with temporal awareness for intelligent intrusion detection in 6G-enabled IIoT networks.
Authors: Guo G; Center for Cyber Security, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia (UKM), UKM Bangi, 43600, Selangor, Malaysia., Qamar F; Center for Cyber Security, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia (UKM), UKM Bangi, 43600, Selangor, Malaysia. faizanqamar@ukm.edu.my., Kazmi SHA; Center for Cyber Security, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia (UKM), UKM Bangi, 43600, Selangor, Malaysia., Ali FM; Center for Software Technology and Management, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia (UKM), UKM Bangi, 43600, Selangor, Malaysia., Ali I; Department of Computer Science, Southeast Missouri State University, Cape Girardeau, 63701, MO, USA.
Source: Scientific reports [Sci Rep] 2026 Mar 14; Vol. 16 (1). Date of Electronic Publication: 2026 Mar 14.
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/s41598-026-43058-x