GEMLIDS-MIOT: A Green Effective Machine Learning Intrusion Detection System based on Federated Learning for Medical IoT network security hardening

Author:

Ioannou IacovosORCID,Nagaradjane Prabagarane,Angin Pelin,Balasubramanian Palaniappan,Kavitha Karthick Jeyagopal,Murugan Palani,Vassiliou Vasos

Funder

Orta Doğu Teknik Üniversitesi

Horizon 2020 Framework Programme

Horizon 2020

Directorate General for European Programmes, Coordination and Development

Publisher

Elsevier BV

Reference90 articles.

1. Machine-learning classifiers for security in connected medical devices;Gao,2017

2. Intrusion detection based on stacked autoencoder for connected healthcare systems;He;IEEE Netw.,2019

3. HEKA: A novel intrusion detection system for attacks to personal medical devices;Newaz,2020

4. Distributed intrusion detection using mobile agents in wireless body area networks;Odesile,2017

5. An effective feature engineering for DNN using hybrid PCA-GWO for intrusion detection in IoMT architecture;R.M.;Comput. Commun.,2020

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