A hybrid deep learning framework for Arabic smishing detection: Dataset creation, model design, and explainability

Mohammed Rasol Al Saidat, Khaled Shaalan, Suleiman Y. Yerima

Open source

DOI
10.1016/j.nlp.2026.100222
Published
09
Container
Natural Language Processing Journal
Publisher
Not recorded
Open access
yes

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BibTeX

@article{allodium:10.1016/j.nlp.2026.100222,
  title = {A hybrid deep learning framework for Arabic smishing detection: Dataset creation, model design, and explainability},
  author = {Mohammed Rasol Al Saidat and Khaled Shaalan and Suleiman Y. Yerima},
  year = {2026},
  journal = {Natural Language Processing Journal},
  doi = {10.1016/j.nlp.2026.100222},
  url = {https://doi.org/10.1016/j.nlp.2026.100222}
}

RIS

TY  - JOUR
TI  - A hybrid deep learning framework for Arabic smishing detection: Dataset creation, model design, and explainability
AU  - Mohammed Rasol Al Saidat
AU  - Khaled Shaalan
AU  - Suleiman Y. Yerima
PY  - 2026
JO  - Natural Language Processing Journal
DO  - 10.1016/j.nlp.2026.100222
UR  - https://doi.org/10.1016/j.nlp.2026.100222
ER  - 

APA

Saidat, M. R. A., Shaalan, K., & Yerima, S. Y. (2026). A hybrid deep learning framework for Arabic smishing detection: Dataset creation, model design, and explainability. Natural Language Processing Journal. https://doi.org/10.1016/j.nlp.2026.100222

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