A Comprehensive Review of Machine Learning-Based Intrusion Detection Techniques for IoT Networks-Reference-Cited by-同舟云学术

A Comprehensive Review of Machine Learning-Based Intrusion Detection Techniques for IoT Networks

Published:2023 Issue: Volume: Page:465-473
ISSN:1860-949X
Container-title:Studies in Computational Intelligence
language:
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Author:

Samara Ghassan,Aljaidi Mohammad,Alazaidah Raed,Qasem Mais Haj,Hassan Mohammad,Al-Milli Nabeel,Al-Batah Mohammad S.,Kanan Mohammad

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-43300-9_38

Reference22 articles.

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3. Kanan, M., Habib, M.S., Habib, T., Zahoor, S., Gulzar, A., Raza, H., Abusaq, Z.: A flexible robust possibilistic programming approach for sustainable second-generation biogas supply chain design under multiple uncertainties. Sustainability 14, 11597 (2022). https://doi.org/10.3390/su141811597

4. Abusaq, Z., Habib, M.S., Shehzad, A., Kanan, M., Assaf, R.: A flexible robust possibilistic programming approach toward wood pellets supply chain network design. Mathematics 10(19), 1–27 (2022)

5. Ghanbari, Z., Navimipour, N.J., Hosseinzadeh, M., Darwesh, A.: Resource allocation mechanisms and approaches on the Internet of Things. Cluster Comput. 1–30 (2019)

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