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作 者:陆苗霞[1] LU Miaoxia(Nanjing Audit University Jinshen College,Nanjing Jiangsu 210023,China)
出 处:《信息与电脑》2023年第16期203-205,共3页Information & Computer
摘 要:随着信息技术的革新和以第五代移动通信技术(5th Generation Mobile Communication Technology,5G)为代表的无线网络技术的快速发展,大量的无线设备需要接入网络。无线网络具有开放式的通信特性,面临着不可忽视的信息安全威胁。射频指纹技术通过分析无线信号中所携带的能够反映发射机硬件固有缺陷的特征,能够唯一地确定该信号的发射机身份。文章提出利用k均值聚类算法分析差分处理的信号,按照每个聚类的中心点的相位大小顺时针排序,输出分类集群的类别内的距离和类别向量的平均距离,作为分类特征向量和识别目标设备的方法。With the innovation of information technology and the rapid development of wireless network technology represented by 5th Generation Mobile Communication Technology(5G),a large number of wireless devices need to access the network.Wireless networks have open communication characteristics and also face information security threats that cannot be ignored.Radio frequency fingerprint technology can uniquely determine the transmitter identity of a wireless signal by analyzing the features carried by the signal that reflect the inherent hardware defects of the transmitter.This article proposes the use of k-means clustering algorithm to analyze differential processed signals,sort them clockwise according to the phase size of the cluster center points of each cluster,output the distance within the category of the classification cluster and the average distance of the category vector as feature vectors for classification and recognition of target devices.
分 类 号:TP309.1[自动化与计算机技术—计算机系统结构]
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