Please use this identifier to cite or link to this item: http://repository.futminna.edu.ng:8080/jspui/handle/123456789/26713
Title: 5G ENABLED INTERNET OF THINGS: A REVIEW
Authors: CHIKEZIE, CHEKWAS IFEANYI
USMAN, ABRAHAM USMAN
DAVID, MICHAEL
ZUBAIR, SULEIMAN
ABDULLAHI, HASSAN MUSA
Keywords: Internet of Things (IoT), Wireless Technologies, Machine Learning (ML).
Issue Date: 31-Dec-2023
Publisher: Harvard Publications
Abstract: The integration of 5G wireless technology and the Internet of Things (IoT) has revolutionized connectivity with high speed, ultra-low latency, and expansive device capacity. This paper explores the potential synergy between 5G and IoT, their role in transforming the IoT landscape, and their applications in smart cities, transportation, and health care. The paper emphasizes the importance of seamless connectivity and real time data exchange across industries and offers an in-depth analysis of the technical features and benefits of 5G technology, such as its ability to transfer large data volumes over shorter distances and support a massive number of connected devices per square kilometer. However, the paper also raises concerns about the extensive attack surface and diverse nature of interconnected devices, which can lead to significant security risks. The paper proposes leveraging machine learning models for intrusion and anomaly detection to fortify the security landscape within the 5G-IoT ecosystem. The fusion of 5G and IoT technologies provides a connected world while necessitating proactive measures to address security concerns.
URI: http://repository.futminna.edu.ng:8080/jspui/handle/123456789/26713
ISSN: 3027-0952
Appears in Collections:Telecommunication Engineering

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