无线物理层识别辅助5G网络安全

Jie Chang, Yihan Xiao, Zhen Zhang
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引用次数: 4

摘要

用于物理层识别安全的特定发射体识别利用发射体的专有特征来区分用于5G网络安全的允许发射体。本文提出了一种基于等高线斯特拉图像的发射器识别方法。本文采集了8台变送器的输出信号来验证我们的方法。利用等高线图像(Contour Stella Image)将信号转化为图像,将信号识别问题转化为图像分类问题。在得到所采集数据集的轮廓Stella图像后。利用卷积神经网络(CNN)对这些图像进行判别,进一步识别出发射机。在本文中,我们使用CNN的Alex-Net。我们也使用传统的方法来区分图像。结果表明,将信号转化为图像来识别个体的方法是有效的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Wireless Physical-Layer Identification Assisted 5G Network Security
The specific emitter identification for physical-layer identification security utilize the exclusive features of the emitter to distinguish permissible emitters for 5G network security. In this paper, we develop an emitter identification based on Contour Stella Image. This paper collects output signal of eight transmitters to validate our method. Contour Stella Image is used to convert signal into a picture and the problem of signal identification turns into picture classification. After getting the Contour Stella Image of the collected dataset. Convolutional Neural Network(CNN) is used to discriminate these picture and identify the transmitters farther. In this paper,we used Alex-Net of CNN. We also use traditional method to distinguish image. The result shows that the method of identifying individuals by transforming signals into pictures is effective.
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