Optimization-driven machine learning intrusion detection systems for resource-constrained internet of things challenges: a systematic review and future directions

Feras Mohammed Al-Matarneh, Bassam Abdo Al-Hameli

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DOI: 10.7717/peerj-cs.4048
Published: 10
Container: PeerJ Computer Science
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.7717/peerj-cs.4048,
  title = {Optimization-driven machine learning intrusion detection systems for resource-constrained internet of things challenges: a systematic review and future directions},
  author = {Feras Mohammed Al-Matarneh and Bassam Abdo Al-Hameli},
  year = {2026},
  journal = {PeerJ Computer Science},
  doi = {10.7717/peerj-cs.4048},
  url = {https://doi.org/10.7717/peerj-cs.4048}
}

RIS

TY  - JOUR
TI  - Optimization-driven machine learning intrusion detection systems for resource-constrained internet of things challenges: a systematic review and future directions
AU  - Feras Mohammed Al-Matarneh
AU  - Bassam Abdo Al-Hameli
PY  - 2026
JO  - PeerJ Computer Science
DO  - 10.7717/peerj-cs.4048
UR  - https://doi.org/10.7717/peerj-cs.4048
ER  -

APA

Al-Matarneh, F. M., & Al-Hameli, B. A. (2026). Optimization-driven machine learning intrusion detection systems for resource-constrained internet of things challenges: a systematic review and future directions. PeerJ Computer Science. https://doi.org/10.7717/peerj-cs.4048

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doaj · retrieved 2026-11-10T18:07:42.995Z