Enhancing Cybersecurity: Hybrid Deep Learning Approaches to Smishing Attack Detection

Tanjim Mahmud, Md. Alif Hossen Prince, Md. Hasan Ali, Mohammad Shahadat Hossain, Karl Andersson

Open source

DOI: 10.3390/systems12110490
Published: 2024-11-14
Container: Systems
Publisher: MDPI AG
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.3390/systems12110490,
  title = {Enhancing Cybersecurity: Hybrid Deep Learning Approaches to Smishing Attack Detection},
  author = {Tanjim Mahmud and Md. Alif Hossen Prince and Md. Hasan Ali and Mohammad Shahadat Hossain and Karl Andersson},
  year = {2024},
  journal = {Systems},
  doi = {10.3390/systems12110490},
  url = {https://doi.org/10.3390/systems12110490}
}

RIS

TY  - JOUR
TI  - Enhancing Cybersecurity: Hybrid Deep Learning Approaches to Smishing Attack Detection
AU  - Tanjim Mahmud
AU  - Md. Alif Hossen Prince
AU  - Md. Hasan Ali
AU  - Mohammad Shahadat Hossain
AU  - Karl Andersson
PY  - 2024
JO  - Systems
DO  - 10.3390/systems12110490
UR  - https://doi.org/10.3390/systems12110490
ER  -

APA

Mahmud, T., Prince, M. A. H., Ali, M. H., Hossain, M. S., & Andersson, K. (2024). Enhancing Cybersecurity: Hybrid Deep Learning Approaches to Smishing Attack Detection. Systems. https://doi.org/10.3390/systems12110490

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crossref · retrieved 2026-09-26T03:38:44.925Z