CNN-Based Physical Layer Authentication against Impersonation Attacks 


Vol. 50,  No. 8, pp. 1172-1182, Aug.  2025
10.7840/kics.2025.50.8.1172


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  Abstract

In this paper, we propose a convolutional neural network (CNN)-based physical layer authentication (PLA) scheme as a countermeasure against impersonation attacks in WLAN (Wireless Local Area Network). We evaluate the proposed PLA scheme in terms of attack detection rate through experiments. The main contributions are as follows: (1) We implement the Evil Twin attack which is one of the impersonation attacks in WLAN; (2) We implement the channel state information (CSI)-based PLA scheme and perform experiments to measure attack detection rates in both static and dynamic channel environments; (3) We finally propose the CNN-based PLA scheme exploiting the unique IQ imbalance of hardware and evaluate its performance through extensive simulations.

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[IEEE Style]

H. Oh, J. Yoon, J. Moon, T. Kim, I. Bang, "CNN-Based Physical Layer Authentication against Impersonation Attacks," The Journal of Korean Institute of Communications and Information Sciences, vol. 50, no. 8, pp. 1172-1182, 2025. DOI: 10.7840/kics.2025.50.8.1172.

[ACM Style]

Hanol Oh, Jihyeon Yoon, Jihwan Moon, Taehoon Kim, and Inkyu Bang. 2025. CNN-Based Physical Layer Authentication against Impersonation Attacks. The Journal of Korean Institute of Communications and Information Sciences, 50, 8, (2025), 1172-1182. DOI: 10.7840/kics.2025.50.8.1172.

[KICS Style]

Hanol Oh, Jihyeon Yoon, Jihwan Moon, Taehoon Kim, Inkyu Bang, "CNN-Based Physical Layer Authentication against Impersonation Attacks," The Journal of Korean Institute of Communications and Information Sciences, vol. 50, no. 8, pp. 1172-1182, 8. 2025. (https://doi.org/10.7840/kics.2025.50.8.1172)
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pISSN : 1226 - 4717
eISSN : 2287 - 3880