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Federated learning distributed consensus algorithm for telemedicine

Author(s)
YOUNGBOK CHO Department of Information Security, Affiliation, Korea
Abstract
Recently, as the importance of telemedicine increases due to the COVID-19 pandemic, interest in the safe use of medical data is increasing. The need for safe and effective management of personal information is emerging as the number of hacking cases related to personal information is increasing due to the activation of big data utilization and the activation of telemedicine due to the 4th industrial revolution. In addition, since personal information used in the medical field is classified as sensitive information, it is necessary to focus more on security. However, in order to access one's own medical information in telemedicine and big data environments, it must be provided anytime, anywhere. In Korea, medical information is currently managed in the form of centralization where local hospitals store and manage each patient's data. Therefore, the problem of centralized data management was solved by applying block-chain technology. It provides more free information exchange in cooperative telemedicine and ensures the privacy of patient information while safely reaching mutual agreements
Publication Details
Page(s) 5013-5020
DOI DOI not available
Published Journal: Journal of Theoretical and Applied Information Technology, Volume: 100, Issue: 16, Year: 2022

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Keywords
privacy, telemedicine, Distributed Consensus Algorithm, Black-chain, Federated Learning
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