Federated Learning for IoMT Applications: A Standardization and Benchmarking Framework of Intrusion Detection Systems-Reference-Cited by-同舟云学术

Federated Learning for IoMT Applications: A Standardization and Benchmarking Framework of Intrusion Detection Systems

Published:2023-02 Issue:2 Volume:27 Page:878-887
ISSN:2168-2194
Container-title:IEEE Journal of Biomedical and Health Informatics
language:
Short-container-title:IEEE J. Biomed. Health Inform.

Author:

Alamleh Amneh¹,Albahri O. S.¹^ORCID,Zaidan A. A.²,Albahri A. S.³,Alamoodi A. H.¹,Zaidan B. B.⁴,Qahtan Sarah⁵,Alsatar H. A.¹,Al-Samarraay Mohammed S.¹,Jasim Ali Najm⁶

Affiliation:

1. Department of Comput- ing, Universiti Pendidikan Sultan Idris, Perak, Malaysia

2. Faculty of Engineering and IT, The British University in Dubai, Dubai, United Arab Emirates

3. Informatics Institute for Postgraduate Studies (IIPS), Iraqi Commission for Computers and Informatics (ICCI), Baghdad, Iraq, Taiwan

4. Future Technology Research Center, National Yunlin University of Science and Technology, Yunlin, Taiwan

5. Computer Center, College of Health and Medical Technology, Middle Technical University, Baghdad, Iraq

6. Foundation of Alshuhda, Baghdad, Iraq

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Health Information Management,Electrical and Electronic Engineering,Computer Science Applications,Health Informatics

Link

http://xplorestaging.ieee.org/ielx7/6221020/10036335/09756888.pdf?arnumber=9756888

Reference60 articles.

1. Towards Accurate Anomaly Detection in Industrial Internet-of-Things using Hierarchical Federated Learning

2. Assessment and Comparison of Various MCDM Approaches in the Selection of Manufacturing Process

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

4. The original Borda count and partial voting

5. EPPDA: An Efficient Privacy-Preserving Data Aggregation Federated Learning Scheme

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