Intrusion detection with HACDT-Net and TRBM-Net using a hybrid deep learning framework with enhanced sampling techniques.
- DOI
- 10.1038/s41598-026-41422-5
- Published
- 2026 Mar 3
- Container
- Scientific reports
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1038/s41598-026-41422-5,
title = {Intrusion detection with HACDT-Net and TRBM-Net using a hybrid deep learning framework with enhanced sampling techniques.},
author = {Padma Priya N and Mohanbabu G},
year = {2026},
journal = {Scientific reports},
doi = {10.1038/s41598-026-41422-5},
url = {https://doi.org/10.1038/s41598-026-41422-5}
}RIS
TY - JOUR TI - Intrusion detection with HACDT-Net and TRBM-Net using a hybrid deep learning framework with enhanced sampling techniques. AU - Padma Priya N AU - Mohanbabu G PY - 2026 JO - Scientific reports DO - 10.1038/s41598-026-41422-5 UR - https://doi.org/10.1038/s41598-026-41422-5 ER -
APA
N, P. P., & G, M. (2026). Intrusion detection with HACDT-Net and TRBM-Net using a hybrid deep learning framework with enhanced sampling techniques.. Scientific reports. https://doi.org/10.1038/s41598-026-41422-5
Source records
- pubmed · retrieved 2026-09-25T22:45:59.972Z