Chapter 2 - Supervised machine learning techniques to protect IoT healthcare environment against cyberattacks

Document Type

Book Chapter

Source of Publication

Intelligent Edge Computing for Cyber Physical Applications

Publication Date

1-1-2023

Abstract

The Internet of Things (IoT) have become the central technology of the current years. Almost all industries are amalgamating the IoT in their production to enhance the outcome of their businesses. Healthcare organizations, in particular, are taking advantage of the services provided by the IoT, known as the Internet of Medical Things (IoMT), to enhance the healthcare systems by moving from manual management systems to computerized systems professional storage. Connecting doctors, nurses, and patients for information exchange is the aim of applications on mobile devices. Thus all collected data is stored in healthcare storage systems. Since cyberattacks on healthcare systems are overgrowing, creating robust systems to secure patients’ confidential information is crucial. This chapter includes a deeper understanding of the integration of IoT in health informatics and medical services. It introduces supervised machine learning techniques for health datasets showing how machine-learning techniques help in increasing the healthcare system’s security by discovering attacks and analyzing their behaviors. The results obtained from this study are compared and discussed in this chapter with the results of previous research works. Finally, some future challenges and studies related to the contribution of IoT security in the health informatics and medical services fields are proposed.

ISBN

9780323994125

Publisher

Elsevier

First Page

17

Last Page

34

Disciplines

Computer Sciences

Keywords

Supervised learning, internet of things, healthcare informatics, medical services, cyberattacks, security

Indexed in Scopus

no

Open Access

no

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