无线射频识别(Radio Frequency Identification,RFID)系统最基本的功能是标签识别,然而身份验证系统无法检测到伪造或克隆标签,从而出现潜在安全隐患和个人隐私问题。目前有基于加密的认证协议和基于特征提取的解决方法,其中基于加密的...无线射频识别(Radio Frequency Identification,RFID)系统最基本的功能是标签识别,然而身份验证系统无法检测到伪造或克隆标签,从而出现潜在安全隐患和个人隐私问题。目前有基于加密的认证协议和基于特征提取的解决方法,其中基于加密的认证协议方法不兼容现有的协议,基于特征提取的方法存在特征提取困难或者识别距离短等限制。文中基于标签物理层信号的真实性进行识别,结合深度学习技术,提出标签信号识别方法。其核心思想在于在RFID通信过程中,利用标签的后向散射信号提取与标签逻辑信息无关的信号,将提取的信号送入卷积神经网络进行相似度匹配,根据得到的相似度匹配分数与给定的阈值对比,最后实现标签的真实性识别。采用USRP N210作为RFID系统的阅读器,采用150个超高频商用标签作为信号的发射器,并在实际场景中采集真实的RFID信号。通过实验验证了基于深度学习的标签识别能达到94%以上的识别精度,在识别距离长达2 m的情况下其等错误比率(EER)为0.034。展开更多
With the increasing pervasiveness of mobile devices such as smartphones,smart TVs,and wearables,smart sensing,transforming the physical world into digital information based on various sensing medias,has drawn research...With the increasing pervasiveness of mobile devices such as smartphones,smart TVs,and wearables,smart sensing,transforming the physical world into digital information based on various sensing medias,has drawn researchers’great attention.Among different sensing medias,WiFi and acoustic signals stand out due to their ubiquity and zero hardware cost.Based on different basic principles,researchers have proposed different technologies for sensing applications with WiFi and acoustic signals covering human activity recognition,motion tracking,indoor localization,health monitoring,and the like.To enable readers to get a comprehensive understanding of ubiquitous wireless sensing,we conduct a survey of existing work to introduce their underlying principles,proposed technologies,and practical applications.Besides we also discuss some open issues of this research area.Our survey reals that as a promising research direction,WiFi and acoustic sensing technologies can bring about fancy applications,but still have limitations in hardware restriction,robustness,and applicability.展开更多
文摘无线射频识别(Radio Frequency Identification,RFID)系统最基本的功能是标签识别,然而身份验证系统无法检测到伪造或克隆标签,从而出现潜在安全隐患和个人隐私问题。目前有基于加密的认证协议和基于特征提取的解决方法,其中基于加密的认证协议方法不兼容现有的协议,基于特征提取的方法存在特征提取困难或者识别距离短等限制。文中基于标签物理层信号的真实性进行识别,结合深度学习技术,提出标签信号识别方法。其核心思想在于在RFID通信过程中,利用标签的后向散射信号提取与标签逻辑信息无关的信号,将提取的信号送入卷积神经网络进行相似度匹配,根据得到的相似度匹配分数与给定的阈值对比,最后实现标签的真实性识别。采用USRP N210作为RFID系统的阅读器,采用150个超高频商用标签作为信号的发射器,并在实际场景中采集真实的RFID信号。通过实验验证了基于深度学习的标签识别能达到94%以上的识别精度,在识别距离长达2 m的情况下其等错误比率(EER)为0.034。
基金supported by the National Natural Science Foundation of China under Grant Nos.62172286 and U2001207the Natural Science Foundation of Guangdong Province of China under Grant Nos.2022A1515011509 and 2017A030312008the Guangdong"Pearl River Talent Recruitment Program"under Grant No.2019ZT08X603.
文摘With the increasing pervasiveness of mobile devices such as smartphones,smart TVs,and wearables,smart sensing,transforming the physical world into digital information based on various sensing medias,has drawn researchers’great attention.Among different sensing medias,WiFi and acoustic signals stand out due to their ubiquity and zero hardware cost.Based on different basic principles,researchers have proposed different technologies for sensing applications with WiFi and acoustic signals covering human activity recognition,motion tracking,indoor localization,health monitoring,and the like.To enable readers to get a comprehensive understanding of ubiquitous wireless sensing,we conduct a survey of existing work to introduce their underlying principles,proposed technologies,and practical applications.Besides we also discuss some open issues of this research area.Our survey reals that as a promising research direction,WiFi and acoustic sensing technologies can bring about fancy applications,but still have limitations in hardware restriction,robustness,and applicability.
