HiddenTag:Enabling Person Identification Without Privacy Exposure

作     者：QIU Chen DAI Tao GUO Bin YU Zhiwen LIU Sicong QIU Chen;DAI Tao;GUO Bin;YU Zhiwen;LIU Sicong

作者机构：Northwestern Polytechnical UniversityXi’an 710072China Chang’an UniversityXi’an 710064China 

出 版 物：《ZTE Communications》 (中兴通讯技术（英文版）)

年 卷 期：2021年第19卷第3期

页      面：3-12页

学科分类：08[工学] 0839[工学-网络空间安全] 081201[工学-计算机系统结构] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：person identification acoustic sensing CSI smart home 

摘      要：Person identification is the key to enable personalized services in smart homes,including the smart voice assistant,augmented reality,and targeted *** research in the past decades in person identification has brought technologies with high accuracy,existing solutions either require explicit user interaction or rely on images and video processing,and thus suffer from cost and privacy *** this paper,we introduce a devicefree personal identification system–HiddenTag,which utilizes smartphones to identify different users via profiling indoor activities with inaudible sound and channel state information(CSI).HiddenTag sends inaudible sound and senses its diffraction and multi-path reflection using *** upon the multi-path effects and human body absorption,we design suitable sound signals and acoustic features for constructing the human body *** addition,we use CSI to trigger the system of acoustic *** experiments indicate that HiddenTag can distinguish multi-person in 10–15 s with 95.1%*** implement a prototype of HiddenTag with an online system by Android smartphones and maintain 84%–90%online accuracy.