Blockchain-Enabled Federated Learning for Privacy and Security

Sukanya, Prof M; Kavipriya, MS A

ISBN 10: 6209074316 ISBN 13: 9786209074318

Edit� par LAP LAMBERT Academic Publishing, 2025

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Titre : Blockchain-Enabled Federated Learning for ...
�diteur : LAP LAMBERT Academic Publishing
Date d'�dition : 2025
Reliure : PAP
Etat : New

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Blockchain-Enabled Federated Learning for Privacy and Security

M. Sukanya (u. a.)

Edit� par LAP LAMBERT Academic Publishing, 2025

ISBN 10 : 6209074316 ISBN 13 : 9786209074318

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Blockchain-Enabled Federated Learning for Privacy and Security

M. Sukanya

Edit� par LAP LAMBERT Academic Publishing Okt 2025, 2025

ISBN 10 : 6209074316 ISBN 13 : 9786209074318

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Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -The book 'Blockchain-Enabled Federated Learning for Privacy and Security' explores the integration of blockchain technology and federated learning to address critical challenges in healthcare data sharing. With the rise of electronic health records, medical imaging, IoMT devices, and genomics, safeguarding patient privacy while enabling collaborative AI has become essential. Blockchain provides decentralization, immutability, and trust, while federated learning ensures model training without exposing raw data. Together, they form a privacy-preserving, auditable, and scalable framework for healthcare AI. The book covers fundamentals, system architectures, cryptographic techniques, and performance trade-offs, along with real-world case studies in cancer research, IoMT, and COVID-19 diagnosis. It highlights regulatory and ethical considerations such as GDPR, HIPAA, and India's DPDP Act, and proposes future research in quantum integration, explainable AI, fairness-aware FL, and governance through smart contracts. This comprehensive guide serves researchers, healthcare professionals, and policymakers in building secure, transparent, and patient-centric healthcare ecosystems.VDM Verlag, Dudweiler Landstra�e 99, 66123 Saarbr�cken 72 pp. Englisch. N� de r�f. du vendeur 9786209074318

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Blockchain-Enabled Federated Learning for Privacy and Security

Prof. M. Sukanya

Edit� par Omniscriptum, LAP Lambert Academic Publishing, 2025

ISBN 10 : 6209074316 ISBN 13 : 9786209074318

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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The book 'Blockchain-Enabled Federated Learning for Privacy and Security' explores the integration of blockchain technology and federated learning to address critical challenges in healthcare data sharing. With the rise of electronic health records, medical imaging, IoMT devices, and genomics, safeguarding patient privacy while enabling collaborative AI has become essential. Blockchain provides decentralization, immutability, and trust, while federated learning ensures model training without exposing raw data. Together, they form a privacy-preserving, auditable, and scalable framework for healthcare AI. The book covers fundamentals, system architectures, cryptographic techniques, and performance trade-offs, along with real-world case studies in cancer research, IoMT, and COVID-19 diagnosis. It highlights regulatory and ethical considerations such as GDPR, HIPAA, and India's DPDP Act, and proposes future research in quantum integration, explainable AI, fairness-aware FL, and governance through smart contracts. This comprehensive guide serves researchers, healthcare professionals, and policymakers in building secure, transparent, and patient-centric healthcare ecosystems. 72 pp. Englisch. N� de r�f. du vendeur 9786209074318

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Blockchain-Enabled Federated Learning for Privacy and Security

M. Sukanya

Edit� par LAP LAMBERT Academic Publishing, 2025

ISBN 10 : 6209074316 ISBN 13 : 9786209074318

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Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The book 'Blockchain-Enabled Federated Learning for Privacy and Security' explores the integration of blockchain technology and federated learning to address critical challenges in healthcare data sharing. With the rise of electronic health records, medical imaging, IoMT devices, and genomics, safeguarding patient privacy while enabling collaborative AI has become essential. Blockchain provides decentralization, immutability, and trust, while federated learning ensures model training without exposing raw data. Together, they form a privacy-preserving, auditable, and scalable framework for healthcare AI. The book covers fundamentals, system architectures, cryptographic techniques, and performance trade-offs, along with real-world case studies in cancer research, IoMT, and COVID-19 diagnosis. It highlights regulatory and ethical considerations such as GDPR, HIPAA, and India's DPDP Act, and proposes future research in quantum integration, explainable AI, fairness-aware FL, and governance through smart contracts. This comprehensive guide serves researchers, healthcare professionals, and policymakers in building secure, transparent, and patient-centric healthcare ecosystems. N� de r�f. du vendeur 9786209074318

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Blockchain-Enabled Federated Learning for Privacy and Security

Sukanya, Prof M; Kavipriya, MS A

Edit� par LAP LAMBERT Academic Publishing, 2025

ISBN 10 : 6209074316 ISBN 13 : 9786209074318

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PAP. Etat : New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. N� de r�f. du vendeur L0-9786209074318

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Blockchain-Enabled Federated Learning for Privacy and Security (Paperback)

Prof M. Sukanya

Edit� par LAP Lambert Academic Publishing, 2025

ISBN 10 : 6209074316 ISBN 13 : 9786209074318

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Paperback. Etat : new. Paperback. The book "Blockchain-Enabled Federated Learning for Privacy and Security" explores the integration of blockchain technology and federated learning to address critical challenges in healthcare data sharing. With the rise of electronic health records, medical imaging, IoMT devices, and genomics, safeguarding patient privacy while enabling collaborative AI has become essential. Blockchain provides decentralization, immutability, and trust, while federated learning ensures model training without exposing raw data. Together, they form a privacy-preserving, auditable, and scalable framework for healthcare AI. The book covers fundamentals, system architectures, cryptographic techniques, and performance trade-offs, along with real-world case studies in cancer research, IoMT, and COVID-19 diagnosis. It highlights regulatory and ethical considerations such as GDPR, HIPAA, and India's DPDP Act, and proposes future research in quantum integration, explainable AI, fairness-aware FL, and governance through smart contracts. This comprehensive guide serves researchers, healthcare professionals, and policymakers in building secure, transparent, and patient-centric healthcare ecosystems. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N� de r�f. du vendeur 9786209074318

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Blockchain-Enabled Federated Learning for Privacy and Security

Sukanya, Prof M; Kavipriya, MS A

Edit� par LAP Lambert Academic Publishing, 2025

ISBN 10 : 6209074316 ISBN 13 : 9786209074318

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Blockchain-Enabled Federated Learning for Privacy and Security (Paperback)

Prof M. Sukanya

Edit� par LAP Lambert Academic Publishing, 2025

ISBN 10 : 6209074316 ISBN 13 : 9786209074318

Neuf Paperback

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Paperback. Etat : new. Paperback. The book "Blockchain-Enabled Federated Learning for Privacy and Security" explores the integration of blockchain technology and federated learning to address critical challenges in healthcare data sharing. With the rise of electronic health records, medical imaging, IoMT devices, and genomics, safeguarding patient privacy while enabling collaborative AI has become essential. Blockchain provides decentralization, immutability, and trust, while federated learning ensures model training without exposing raw data. Together, they form a privacy-preserving, auditable, and scalable framework for healthcare AI. The book covers fundamentals, system architectures, cryptographic techniques, and performance trade-offs, along with real-world case studies in cancer research, IoMT, and COVID-19 diagnosis. It highlights regulatory and ethical considerations such as GDPR, HIPAA, and India's DPDP Act, and proposes future research in quantum integration, explainable AI, fairness-aware FL, and governance through smart contracts. This comprehensive guide serves researchers, healthcare professionals, and policymakers in building secure, transparent, and patient-centric healthcare ecosystems. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N� de r�f. du vendeur 9786209074318

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Blockchain-Enabled Federated Learning for Privacy and Security (Paperback)

Prof M. Sukanya

Edit� par LAP Lambert Academic Publishing, 2025

ISBN 10 : 6209074316 ISBN 13 : 9786209074318

Neuf Paperback

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Vendeur : AussieBookSeller, Truganina, VIC, Australie

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Paperback. Etat : new. Paperback. The book "Blockchain-Enabled Federated Learning for Privacy and Security" explores the integration of blockchain technology and federated learning to address critical challenges in healthcare data sharing. With the rise of electronic health records, medical imaging, IoMT devices, and genomics, safeguarding patient privacy while enabling collaborative AI has become essential. Blockchain provides decentralization, immutability, and trust, while federated learning ensures model training without exposing raw data. Together, they form a privacy-preserving, auditable, and scalable framework for healthcare AI. The book covers fundamentals, system architectures, cryptographic techniques, and performance trade-offs, along with real-world case studies in cancer research, IoMT, and COVID-19 diagnosis. It highlights regulatory and ethical considerations such as GDPR, HIPAA, and India's DPDP Act, and proposes future research in quantum integration, explainable AI, fairness-aware FL, and governance through smart contracts. This comprehensive guide serves researchers, healthcare professionals, and policymakers in building secure, transparent, and patient-centric healthcare ecosystems. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. N� de r�f. du vendeur 9786209074318

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