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Smart city article details

Title	A Framework For Privacy-Preservation Of Iot Healthcare Data Using Federated Learning And Blockchain Technology
ID_Doc	1776
Authors	Singh S.; Rathore S.; Alfarraj O.; Tolba A.; Yoon B.
Year	2022
Published	Future Generation Computer Systems, 129
DOI	http://dx.doi.org/10.1016/j.future.2021.11.028
Abstract	With the dramatically increasing deployment of IoT (Internet-of-Things) and communication, data has always been a major priority to achieve intelligent healthcare in a smart city. For the modern environment, valuable assets are user IoT data. The privacy policy is even the biggest necessity to secure user's data in a deep-rooted fundamental infrastructure of network and advanced applications, including smart healthcare. Federated learning acts as a special machine learning technique for privacy-preserving and offers to contextualize data in a smart city. This article proposes Blockchain and Federated Learning-enabled Secure Architecture for Privacy-Preserving in Smart Healthcare, where Blockchain-based IoT cloud platforms are used for security and privacy. Federated Learning technology is adopted for scalable machine learning applications like healthcare. Furthermore, users can obtain a well-trained machine learning model without sending personal data to the cloud. Moreover, it also discussed the applications of federated learning for a distributed secure environment in a smart city. © 2021
Author Keywords	Blockchain; Federated Learning; Internet-of-Things; Privacy-preserving

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