Open Access

REVIEW

Navigating IoT Security: Insights into Architecture, Key Security Features, Attacks, Current Challenges and AI-Driven Solutions Shaping the Future of Connectivity

by Ali Hassan¹, N. Nizam-Uddin², Asim Quddus³, Syed Rizwan Hassan⁴, Ateeq Ur Rehman^5,*, Salil Bharany⁶

1 Department of Electrical Engineering, HITEC University, Taxila, 47080, Pakistan
2 Department of Biomedical Engineering, HITEC University, Taxila, 47080, Pakistan
3 Department of Electronics Engineering, University of Chakwal, Chakwal, 48800, Pakistan
4 Department of Computer Science, NFC Institute of Engineering and Fertilizer Research, Faisalabad, 38000, Pakistan
5 School of Computing, Gachon University, Seongnam-si, 13120, Republic of Korea
6 Chitkara University Institute of Engineering and Technology, Chitkara University, Rajpura, 140401, Punjab, India

* Corresponding Author: Ateeq Ur Rehman. Email:

Computers, Materials & Continua 2024, 81(3), 3499-3559. https://doi.org/10.32604/cmc.2024.057877

Received 29 August 2024; Accepted 11 November 2024; Issue published 19 December 2024

Abstract

Enhancing the interconnection of devices and systems, the Internet of Things (IoT) is a paradigm-shifting technology. IoT security concerns are still a substantial concern despite its extraordinary advantages. This paper offers an extensive review of IoT security, emphasizing the technology’s architecture, important security elements, and common attacks. It highlights how important artificial intelligence (AI) is to bolstering IoT security, especially when it comes to addressing risks at different IoT architecture layers. We systematically examined current mitigation strategies and their effectiveness, highlighting contemporary challenges with practical solutions and case studies from a range of industries, such as healthcare, smart homes, and industrial IoT. Our results highlight the importance of AI methods that are lightweight and improve security without compromising the limited resources of devices and computational capability. IoT networks can ensure operational efficiency and resilience by proactively identifying and countering security risks by utilizing machine learning capabilities. This study provides a comprehensive guide for practitioners and researchers aiming to understand the intricate connection between IoT, security challenges, and AI-driven solutions.

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Keywords

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