Federated and Transfer Learning-Empowered Intrusion Detection for IoT Applications

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Otoum, Yazan, et al. “Federated and Transfer Learning-Empowered Intrusion Detection for IoT Applications”. IEEE Internet of Things Magazine, vol. 5, no. 3, 2022, pp. 50-54, https://doi.org/10.1109/iotm.001.2200048.
Otoum, Y., Chamola, V., & Nayak, A. (2022). Federated and Transfer Learning-Empowered Intrusion Detection for IoT Applications. IEEE Internet of Things Magazine, 5(3), 50-54. https://doi.org/10.1109/iotm.001.2200048
Otoum Y, Chamola V, Nayak A. Federated and Transfer Learning-Empowered Intrusion Detection for IoT Applications. IEEE Internet of Things Magazine. 2022;5(3):50-4.
Refrences
Title Journal Journal Categories Citations Publication Date
A Survey on Federated Learning: The Journey from Centralized to Distributed On-Site Learning and Beyond 2020
Multi-Stage Deep Transfer Learning for EMIOT-Enabled Human-Computer Interaction 2022
10.1109/JIOT.2022.3144450
10.1109/LCOMM.2022.3140273
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  • Technology: Electrical engineering. Electronics. Nuclear engineering: Electronics: Computer engineering. Computer hardware
  • Science: Mathematics: Instruments and machines: Electronic computers. Computer science
  • Technology: Electrical engineering. Electronics. Nuclear engineering: Electric apparatus and materials. Electric circuits. Electric networks
  • Science: Mathematics: Instruments and machines: Electronic computers. Computer science
  • Science: Mathematics: Instruments and machines: Electronic computers. Computer science: Computer software
  • Technology: Electrical engineering. Electronics. Nuclear engineering: Electronics: Computer engineering. Computer hardware
  • Science: Mathematics: Instruments and machines: Electronic computers. Computer science
 19 2021