Significance of Machine Learning-Driven Algorithms for Effective Discrimination of DDoS Traffic Within IoT Systems

Mohammed N. Alenezi

Open source

DOI: 10.3390/fi17060266
Published: 06
Container: Future Internet
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.3390/fi17060266,
  title = {Significance of Machine Learning-Driven Algorithms for Effective Discrimination of DDoS Traffic Within IoT Systems},
  author = {Mohammed N. Alenezi},
  year = {2025},
  journal = {Future Internet},
  doi = {10.3390/fi17060266},
  url = {https://doi.org/10.3390/fi17060266}
}

RIS

TY  - JOUR
TI  - Significance of Machine Learning-Driven Algorithms for Effective Discrimination of DDoS Traffic Within IoT Systems
AU  - Mohammed N. Alenezi
PY  - 2025
JO  - Future Internet
DO  - 10.3390/fi17060266
UR  - https://doi.org/10.3390/fi17060266
ER  -

APA

Alenezi, M. N. (2025). Significance of Machine Learning-Driven Algorithms for Effective Discrimination of DDoS Traffic Within IoT Systems. Future Internet. https://doi.org/10.3390/fi17060266

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doaj · retrieved 2026-11-10T07:27:02.409Z