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A Novel IoT Architecture, Assessment of Threats and Their Classification with Machine Learning Solutions

Oliva Debnath1, Saptarshi Debnath1, Sreyashi Karmakar2, MD Tausif Mallick3, Himadri Nath Saha4,*

1 Department of Computer Science and Engineering, Institute of Engineering & Management, Kolkata, 700091, India
2 Department of Information Technology, RCC Institute of Information Technology, Kolkata, 700015, India
3 Department of AK Choudhury, School of Information Technology, University of Calcutta, Kolkata, 700098, India
4 Department of Computer Science, Surendranath Evening College, University of Calcutta, Kolkata, 700009, India

* Corresponding Author: Himadri Nath Saha. Email: email

Journal on Internet of Things 2023, 5, 13-43. https://doi.org/10.32604/jiot.2023.039391

Abstract

The Internet of Things (IoT) will significantly impact our social and economic lives in the near future. Many Internet of Things (IoT) applications aim to automate multiple tasks so inactive physical objects can behave independently of others. IoT devices, however, are also vulnerable, mostly because they lack the essential built-in security to thwart attackers. It is essential to perform the necessary adjustments in the structure of the IoT systems in order to create an end-to-end secure IoT environment. As a result, the IoT designs that are now in use do not completely support all of the advancements that have been made to include sophisticated features in IoT, such as Cloud computing, machine learning techniques, and lightweight encryption techniques. This paper presents a detailed analysis of the security requirements, attack surfaces, and security solutions available for IoT networks and suggests an innovative IoT architecture. The Seven-Layer Architecture in IoT provides decent attack detection accuracy. According to the level of risk they pose, the security threats in each of these layers have been properly categorized, and the essential evaluation criteria have been developed to evaluate the various threats. Also, Machine Learning algorithms like Random Forest and Support Vector Machines, etc., and Deep Learning algorithms like Artificial Neural Networks, Q Learning models, etc., are implemented to overcome the most damaging threats posing security breaches to the different IoT architecture layers.

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Cite This Article

APA Style
Debnath, O., Debnath, S., Karmakar, S., Mallick, M.T., Saha, H.N. (2023). A novel iot architecture, assessment of threats and their classification with machine learning solutions. Journal on Internet of Things, 5(1), 13-43. https://doi.org/10.32604/jiot.2023.039391
Vancouver Style
Debnath O, Debnath S, Karmakar S, Mallick MT, Saha HN. A novel iot architecture, assessment of threats and their classification with machine learning solutions. J Internet Things . 2023;5(1):13-43 https://doi.org/10.32604/jiot.2023.039391
IEEE Style
O. Debnath, S. Debnath, S. Karmakar, M.T. Mallick, and H.N. Saha "A Novel IoT Architecture, Assessment of Threats and Their Classification with Machine Learning Solutions," J. Internet Things , vol. 5, no. 1, pp. 13-43. 2023. https://doi.org/10.32604/jiot.2023.039391



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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