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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Mon, S.F.A., Jones, G.M., Winster, S.G. (2023). Role of Machine Learning and Deep Learning Applications in the Internet of Things (IoT) Security. In: Dhanaraj, R.K., Rawal, B.S., Krishnamoorthi, S., Balusamy, B. (eds) Artificial Intelligence in IoT and Cyborgization. Studies in Computational Intelligence, vol 1103. Springer, Singapore. https://doi.org/10.1007/978-981-99-4303-6_3
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DOI: https://doi.org/10.1007/978-981-99-4303-6_3
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