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Deep support vector data description based physical layer authentication
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DOI：10.23919/JCC.fa.2021-0169.202510.png)
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Abstract
En 中文
In wireless communication, the problem of authenticating the transmitter’s identity is challenging, especially for those terminal devices in which the security schemes based on cryptography are approximately unfeasible owing to limited resources. In this paper, a physical layer authentication scheme is proposed to detect whether there is anomalous access by the attackers disguised as legitimate users. Explicitly, channel state information (CSI) is used as a form of fingerprint to exploit spatial discrimination among devices in the wireless network and machine learning (ML) technology is employed to promote the improvement of authentication accuracy. Considering that the falsified messages are not accessible for authenticator during the training phase, deep support vector data description (Deep SVDD) is selected to solve the one-class classification (OCC) problem. Simulation results show that Deep SVDD based scheme can tackle the challenges of physical layer authentication in wireless communication environments.
Keywords:
deep support vector data description
one-class classification
physical layer authentication
wireless security
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