Advancing Federated Learning Through Novel Mechanism for Privacy Preservation in Healthcare Applications-Reference-Cited by-同舟云学术

Advancing Federated Learning Through Novel Mechanism for Privacy Preservation in Healthcare Applications

Published:2023 Issue: Volume:11 Page:83562-83579
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Abaoud Mohammed¹,Almuqrin Muqrin A.²,Khan Mohammad Faisal³^ORCID

Affiliation:

1. Department of Mathematics and Statistics, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, Saudi Arabia

2. Department of Mathematics, College of Science in Zulfi, Majmaah University, Al-Majmaah, Saudi Arabia

3. Department of Basic Sciences, College of Science and Theoretical studies, Saudi Electronic University, Riyadh, Saudi Arabia

Funder

Deputyship for Research & Innovation, Ministry of Education in Saudi Arabia

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10201859.pdf?arnumber=10201859

Reference46 articles.

1. Smart healthcare surveillance system using IoT and machine learning approaches for heart disease;basak;Proc Advancements Smart Comput Inf Secur 1st Int Conf (ASCIS),2023

2. Security and Privacy in IoT Smart Healthcare

3. 3D Printed Pharmaceutical Systems for Personalized Treatment in Metabolic Syndrome

4. hOCBS: A privacy-preserving blockchain framework for healthcare data leveraging an on-chain and off-chain system design

5. AutoTrust: A privacy-enhanced trust-based intrusion detection approach for internet of smart things

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4. Data Privacy in the Digital Era: Machine Learning Solutions for Confidentiality;E3S Web of Conferences;2024

5. Anonymous and Efficient Authentication Scheme for Privacy-Preserving Federated Cross Learning;Lecture Notes in Computer Science;2024