Privacy Protection of Healthcare Data over Social Networks Using Machine Learning Algorithms

With the rapid development of mobile medical care, medical institutions also have the hidden danger of privacy leakage while sharing personal medical data. Based on the k-anonymity and l-diversity supervised models, it is proposed to use the classified personalized entropy l-diversity privacy protec...

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Veröffentlicht in:	Computational intelligence and neuroscience Jg. 2022; S. 1 - 8
Hauptverfasser:	Khan, Shakir, Saravanan, V., N, Gnanaprakasam C., Lakshmi, T. Jaya, Deb, Nabamita, Othman, Nashwan Adnan
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States Hindawi 24.03.2022 John Wiley & Sons, Inc
Schlagworte:	Algorithms Analysis Computer Security Customization Data analysis Data exchange Data mining Data retrieval Delivery of Health Care Diabetes Entropy (Information theory) Graphs Health care Health care facilities Health services Influenza Information management Information sharing Leakage Machine Learning Medical research Patients Privacy Privacy, Right of Social discrimination learning Social Networking Social networks Social organization Wireless networks
ISSN:	1687-5265, 1687-5273, 1687-5273
Online-Zugang:	Volltext
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