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International Journal of Information Security

Erschienen in:

28.12.2023 | Regular Contribution

Radio frequency fingerprinting techniques for device identification: a survey

verfasst von: Sohail Abbas, Manar Abu Talib, Qassim Nasir, Sally Idhis, Mariam Alaboudi, Ali Mohamed

Erschienen in: International Journal of Information Security | Ausgabe 2/2024

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Abstract

The Internet of Things (IoT) paradigm and the advanced wireless technologies of 5G and beyond are expected to enable diverse applications such as autonomous driving, industrial automation, and smart cities. These applications bring together a vast and diverse IoT device population that occupy radio frequency spectrum. Such a large number of wireless devices expose previously unheard-of threat surfaces in addition to the bandwidth shortage and throughput issues. Device identification is crucial in such scenarios not only to authenticate and authorize nodes, but also to employ different network services. One of the promising solutions for device identification is the use of radio frequency (RF) fingerprinting. Recently, wireless device identification using RF fingerprinting along with machine learning and deep learning technologies showed outstanding results in the recent contemporary domains. This paper presents a systematic literature review of RF fingerprinting identification of wireless devices by presenting the results as a graphical and tabular representation of statistical data obtained. Only experimental research papers were considered of over 130 journals and international conference papers that have been classified and evaluated from the year 2010 till date. This survey focuses on exploring the commonly used RF fingerprinting approaches, feature extraction and filtration techniques, and classification algorithm used in the device identification. Finally, open issues and challenges along with future directions have presented which were discovered during the process of analyzing the literature.

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Titel: Radio frequency fingerprinting techniques for device identification: a survey
verfasst von: Sohail Abbas
Manar Abu Talib
Qassim Nasir
Sally Idhis
Mariam Alaboudi
Ali Mohamed
Publikationsdatum: 28.12.2023
Verlag: Springer Berlin Heidelberg
Erschienen in: International Journal of Information Security / Ausgabe 2/2024
Print ISSN: 1615-5262
Elektronische ISSN: 1615-5270
DOI: https://doi.org/10.1007/s10207-023-00801-z

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