Improving Wireless Network Security Based On Radio Fingerprinting

作者：Yun Lin, Jie Chang · 年份：2019 · DOI：10.1109/qrs-c.2019.00076 · 被引用次数：11 · 研究领域：Wireless Signal Modulation Classification、Digital Media Forensic Detection、Speech and Audio Processing

With the rapid development of the popularity of wireless networks, there are also increasing security threats that follow, and wireless network security issues are becoming increasingly important. Radio frequency fingerprints generated by device tolerance in wireless device transmitters have physical characteristics that are difficult to clone, and can be used for identity authentication of wireless devices. In this paper, we propose a radio frequency fingerprint extraction method based on fractional Fourier transform for transient signals. After getting the features of the signal, we use RPCA to reduce the dimension of the features, and then use KNN to classify them. The results show that when the SNR is 20dB, the recognition rate of this method is close to 100%.