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Demystifying Federated Learning for Blockchain and...

Demystifying Federated Learning for Blockchain and Industrial Internet of Things

Sandeep Kautish, Gaurav Dhiman
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In recent years, mobile technology and the internet of objects have been used in mobile networks to meet new technical demands. Emerging needs have centered on data storage, computation, and low latency management in potentially smart cities, transport, smart grids, and a wide number of sustainable environments. Federated learning's contributions include an effective framework to improve network security in heterogeneous industrial internet of things (IIoT) environments. Demystifying Federated Learning for Blockchain and Industrial Internet of Things rediscovers, redefines, and reestablishes the most recent applications of federated learning using blockchain and IIoT to optimize data for next-generation networks. It provides insights to readers in a way of inculcating the theme that shapes the next generation of secure communication. Covering topics such as smart agriculture, object identification, and educational big data, this premier reference source is an essential resource for computer scientists, programmers, government officials, business leaders and managers, students and faculty of higher education, researchers, and academicians.
Year:
2022
Publisher:
Engineering Science Reference
Language:
english
Pages:
240
ISBN 10:
1668437333
ISBN 13:
9781668437339
File:
EPUB, 17.21 MB
IPFS:
CID , CID Blake2b
english, 2022
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