基于人体通信的可穿戴生物识别认证

Ze-dong Nie, Yuhang Liu, Changjiang Duan, Z. Ruan, Jingzhen Li, Lei Wang
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引用次数: 9

摘要

人体通信(HBC)是在人体附近或体内进行的一种短距离无线通信。本文提出了一种基于电容耦合HBC的可穿戴设备生物识别认证方法。20名志愿者进行了现场实验,以考察其可行性。测量了300 KHz-50 MHz频率范围内HBC信道从一掌到另一掌的S21参数。共采集数据2,561,600条。使用C-SVM和nu-SVM两种支持向量机(SVM)对数据进行分析,其中使用2241400个数据训练SVM模型,使用320200个数据估计认证率。核函数分别采用线性、多项式和径向基函数(RBF)。此外,为了验证低频段特征是否会影响HBC认证的性能,我们将300 KHz ~ 50 MHz、3.4 MHz ~ 50 MHz、5.6 MHz ~ 50 MHz、9.6 MHz ~ 50 MHz四个频段的特征分别作为生物特征特征。实验结果表明,在生物特征识别模式下,识别率达到98%,在生物特征验证模式下,等错误率(EER)为0.24%,受试者工作特征(ROC)的平均曲线下面积(AUC)达到0.9993。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Wearable biometric authentication based on human body communication
Human body communication (HBC) is a short-range, wireless communication in the vicinity of, or inside a human body. In this paper, biometric authentication based on capacitive coupled HBC is presented for the wearable devices. In-situ experiments were conducted with 20 volunteers to investigate the feasibility. The S21 parameters of the HBC channel from one palm to the other within the frequency range of 300 KHz-50 MHz were measured. A total of 2,561,600 data are acquired. The data are analyzed by the support vector machines (SVM) including C-SVM and nu-SVM, where 2,241,400 data are used to train the SVM model and 320,200 data are used to estimate the authentication rate. Linear, polynomial, and radial basis function (RBF) are adopted as the kernel functions, respectively. In addition, to verify whether the features in low frequency band will affect the performance of HBC authentication, the features in four frequency bands, i.e., from 300 KHz to 50 MHz, from 3.4 MHz to 50 MHz, from 5.6 MHz to 50 MHz, and from 9.6 MHz to 50 MHz are used as the biometric trait, respectively. The experiment results show that, in biometric identification mode, identification rate of 98% is achieved, and in biometric verification mode, the equal error rate (EER) is 0.24%, the average area under the curve (AUC) of receiver operating characteristic (ROC) reaches 0.9993.
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