Application of Robust Zero-Watermarking Scheme Based on Federated Learning for Securing the Healthcare Data

The privacy protection and data security problems existing in the healthcare framework based on the Internet of Medical Things (IoMT) have always attracted much attention and need to be solved urgently. In the teledermatology healthcare framework, the smartphone can acquire dermatology medical image...

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Veröffentlicht in:	IEEE journal of biomedical and health informatics Jg. 27; H. 2; S. 804 - 813
Hauptverfasser:	Han, Baoru, Jhaveri, Rutvij H., Wang, Han, Qiao, Dawei, Du, Jinglong
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 01.02.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms Collaborative work Computer Security Data privacy Delivery of Health Care Dermatology Discrete cosine transform Feature extraction Federated learning Health care Humans Image acquisition IoMT Machine learning Medical imaging Medical services Privacy Robustness Security Servers sparse autoencoder network Watermarking Zero-watermarking
ISSN:	2168-2194, 2168-2208, 2168-2208
Online-Zugang:	Volltext
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