Device authentication for 5G terminals via Radio Frequency fingerprints

Abstract

The development of wireless communication network technology has provided people with diversified and convenient services. However, with the expansion of network scale and the increase in the number of devices, malicious attacks on wireless communication are becoming increasingly prevalent, causing significant losses. Currently, wireless communication systems authenticate identities through certain data identifiers. However, this software-based data information can be forged or replicated. This article proposes the authentication of device identity using the hardware fingerprint of the terminal’s Radio Frequency (RF) components, which possesses properties of being genuine, unique, and stable, holding significant implications for wireless communication security. Through the collection and processing of raw data, extraction of various features including time-domain and frequency-domain features, and utilizing machine learning algorithms for training and constructing a legal fingerprint database, it is possible to achieve close to a 97% recognition accuracy for Fifth Generation (5G) terminals of the same model. This provides an additional and robust hardware-based security layer for 5G communication security, enhancing monitoring capability and reliability.

Keywords

Radio Frequency fingerprint / 5G terminal authentication / Wireless security / Mobile communication networks

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

This paper is supported by the National Natural Science Foundation of China (62271280, 62222114, 61925109, and 62071428).

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