Dataset for authentication and authorization using physical layer properties in indoor environment

Ahmed, Kazi Istiaque and Tahir, Mohammad and Lau, Sian Lun and Habaebi, Mohamed Hadi and Ahad, Abdul and Pires, Ivan Miguel (2024) Dataset for authentication and authorization using physical layer properties in indoor environment. Data In Brief, 55. pp. 1-11. ISSN 2352-3409

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Abstract

The proliferation landscape of the Internet of Things (IoT) has accentuated the critical role of Authentication and Authorization (AA) mechanisms in securing interconnected devices. There is a lack of relevant datasets that can aid in building appropriate machine learning enabled security solutions focusing on authentication and authorization using physical layer characteristics. In this context, our research presents a novel dataset derived from real-world scenarios, utilizing Zigbee Zolertia Z1 nodes to capture physical layer properties in indoor environments. The dataset encompasses crucial parameters such as Received Signal Strength Indicator (RSSI), Link Quality Indicator (LQI), Device Internal Temperature, Device Battery Level, and more, providing a comprehensive foundation for ad- vancing Machine learning enabled AA in IoT ecosystems.

Item Type:	Article (Journal)
Uncontrolled Keywords:	RSSI; LQI; Authentication; Authorization; Physical layer; Machine learning; Security; Internet of things;
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5101 Telecommunication. Including telegraphy, radio, radar, television
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Engineering > Department of Electrical and Computer Engineering Kulliyyah of Engineering
Depositing User:	Dr. Mohamed Hadi Habaebi
Date Deposited:	02 Jul 2024 09:12
Last Modified:	02 Jul 2024 09:12
URI:	http://irep.iium.edu.my/id/eprint/112838

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