1. A machine learning multi-hop physical layer authentication with hardware impairments.
- Author
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Ezzati Khatab, Zahra, Mohammadi, Abbas, Pourahmadi, Vahid, and Kuhestani, Ali
- Subjects
MACHINE learning ,CHANNEL estimation ,COMPUTER network security ,MULTI-factor authentication ,HARDWARE ,WIRELESS channels - Abstract
Authentication is one of the major requirements of wireless networks security, which uses to distinguish legal transmitter from illegal transmitter. Physical layer authentication by taking advantages of channel characteristics has become an effective complement to encryption based authentication methods. In this paper, we propose a machine learning relay assisted authentication for dual-hop multiple-input multiple-output (MIMO) systems with hardware impairments. So far, the multi-hop authentication has not been investigated to identify the transmitter at the receiver. Motivated by this, we use channel features for end-to-end authentication. To implement this technique in the practical systems, channel estimation is implemented in the presence of hardware impairments. The neural network is used to recognize the legitimate transmitter from the attacker in this system. Simulation results show that the proposed method provides a significant improvement in authentication performance using the extracted features with neural network method. Numerical results show that the proposed method presents more than 90% authentication accuracy for both of one-hop and two-hop PLA scenarios. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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