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Internet of Healthcare Things: Machine Learning for Security and Privacy

10.00$
Internet of Healthcare Things: Machine Learning for Security and Privacy
BOOK DOWNLOAD

Internet of Healthcare Things: Machine Learning for Security and Privacy

10.00$

(Machine Learning in Biomedical Science and Healthcare Informatics) 1st Edition

by Kavita Sharma (Editor), Yogita Gigras (Editor), Vishnu Sharma (Editor), D. Jude Hemanth (Editor), Ramesh Chandra Poonia (Editor)

INTERNET OF HEALTHCARE THINGSThe book addresses privacy and security issues providing solutions through authentication and authorization mechanisms, blockchain, fog computing, machine learning algorithms, so that machine learning-enabled IoT devices can deliver information concealed in data for fast, computerized responses and enhanced decision-making.

The main objective of this book is to motivate healthcare providers to use telemedicine facilities for monitoring patients in urban and rural areas and gather clinical data for further research. To this end, it provides an overview of the Internet of Healthcare Things (IoHT) and discusses one of the major threats posed by it, which is the data security and data privacy of health records. Another major threat is the combination of numerous devices and protocols, precision time, data overloading, etc. In the IoHT, multiple devices are connected and communicate through certain protocols. Therefore, the application of emerging technologies to mitigate these threats and provide secure data communication over the network is discussed. This book also discusses the integration of machine learning with the IoHT for analyzing huge amounts of data for predicting diseases more accurately. Case studies are also given to verify the concepts presented in the book.

Audience

Researchers and industry engineers in computer science, artificial intelligence, healthcare sector, IT professionals, network administrators, cybersecurity experts.

Year:
2022
Pages:
295
Language:
English
Format:
PDF
Size:
8 MB
ISBN-10:
1119791766
ISBN-13:
978-1119791768, 9781119791768
ASIN:
B09RHQ9L7C
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