An AI-Driven Hybrid Framework for Intrusion Detection in IoT-Enabled E-Health.

Wahab F, Zhao Y, Javeed D, Al-Adhaileh MH, Almaaytah SA, Khan W, Saeed MS, Kumar Shah R

DOI: 10.1155/2022/6096289
Published: 2022
Container: Computational intelligence and neuroscience
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1155/2022/6096289,
  title = {An AI-Driven Hybrid Framework for Intrusion Detection in IoT-Enabled E-Health.},
  author = {Wahab F and Zhao Y and Javeed D and Al-Adhaileh MH and Almaaytah SA and Khan W and Saeed MS and Kumar Shah R},
  year = {2022},
  journal = {Computational intelligence and neuroscience},
  doi = {10.1155/2022/6096289},
  url = {https://doi.org/10.1155/2022/6096289}
}

RIS

TY  - JOUR
TI  - An AI-Driven Hybrid Framework for Intrusion Detection in IoT-Enabled E-Health.
AU  - Wahab F
AU  - Zhao Y
AU  - Javeed D
AU  - Al-Adhaileh MH
AU  - Almaaytah SA
AU  - Khan W
AU  - Saeed MS
AU  - Kumar Shah R
PY  - 2022
JO  - Computational intelligence and neuroscience
DO  - 10.1155/2022/6096289
UR  - https://doi.org/10.1155/2022/6096289
ER  -

APA

F, W., Y, Z., D, J., MH, A., SA, A., W, K., MS, S., & R, K. S. (2022). An AI-Driven Hybrid Framework for Intrusion Detection in IoT-Enabled E-Health.. Computational intelligence and neuroscience. https://doi.org/10.1155/2022/6096289

Source records

pubmed · retrieved 2026-09-25T04:56:32.577Z
europe-pmc · retrieved 2026-09-25T04:56:32.611Z