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Erschienen in:
Introduction to Cyborgization Systems Kapitel lesen Erstes Kapitel lesen

2023 | OriginalPaper | Buchkapitel

Role of Machine Learning and Deep Learning Applications in the Internet of Things (IoT) Security

verfasst von : S. Feslin Anish Mon, G. Maria Jones, S. Godfrey Winster

Erschienen in: Artificial Intelligence in IoT and Cyborgization

Verlag: Springer Nature Singapore

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Abstract

The Internet of Things (IoT) would contain a severe, well organized, and economical and communication effect in our everyday life. Links in IoT channels usually controlled by resources, where cyber-attacks are more likely. Extensive works have proposed to access security and secret issues on IoT channels to address these problems. However, the new characteristics of IoT links are not sufficient to link the top security concerns of IoT systems to present descriptions. Machine Learning (ML) and Deep Learning (DL) methods could give more knowledge of IoT devices that could help overcome different previous security issues. In this chapter, we properly debated security specifications and present security solutions for IoT systems. Then, we provide in-depth of the present ML and DL methods related to additional safety in IoT systems.

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Vorheriges Kapitel AI Based Smart IoT Systems
Nächstes Kapitel IOT Based Experimental Relaying System for Smart Grid
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Metadaten
Titel
Role of Machine Learning and Deep Learning Applications in the Internet of Things (IoT) Security
verfasst von
S. Feslin Anish Mon
G. Maria Jones
S. Godfrey Winster
Copyright-Jahr
2023
Verlag
Springer Nature Singapore
Buch
Artificial Intelligence in IoT and Cyborgization

Print ISBN: 978-981-9943-02-9

Electronic ISBN: 978-981-9943-03-6

Copyright-Jahr: 2023

DOI
https://doi.org/10.1007/978-981-99-4303-6_3

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