Enhancing intrusion detection in encrypted DoH traffic through a robust ensemble learning framework

Hussein Abrahim, Weiyan Hou, Yan Zhuang, Hafeez Ur Rahman

Open source

DOI: 10.1371/journal.pone.0345880
Published: 2026-04-07
Container: PLOS One
Publisher: Public Library of Science (PLoS)
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1371/journal.pone.0345880,
  title = {Enhancing intrusion detection in encrypted DoH traffic through a robust ensemble learning framework},
  author = {Hussein Abrahim and Weiyan Hou and Yan Zhuang and Hafeez Ur Rahman},
  year = {2026},
  journal = {PLOS One},
  doi = {10.1371/journal.pone.0345880},
  url = {https://doi.org/10.1371/journal.pone.0345880}
}

RIS

TY  - JOUR
TI  - Enhancing intrusion detection in encrypted DoH traffic through a robust ensemble learning framework
AU  - Hussein Abrahim
AU  - Weiyan Hou
AU  - Yan Zhuang
AU  - Hafeez Ur Rahman
PY  - 2026
JO  - PLOS One
DO  - 10.1371/journal.pone.0345880
UR  - https://doi.org/10.1371/journal.pone.0345880
ER  -

APA

Abrahim, H., Hou, W., Zhuang, Y., & Rahman, H. U. (2026). Enhancing intrusion detection in encrypted DoH traffic through a robust ensemble learning framework. PLOS One. https://doi.org/10.1371/journal.pone.0345880

Source records

crossref · retrieved 2026-09-25T04:33:22.582Z