Poster: Fingerprint-Face Friction Based Earable Authentication

Z. Wang, Yilin Wang, Yingying Chen, Jie Yang
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Abstract

Ear wearables (earables) have become an emerging and wide acceptable platform for various applications. Because of the limited input interface of earables, traditional authentication methods become less desired. However, the feature-rich sensing abilities of earables and the unique human face-ear channel bring us new sensing opportunities to reutilize fingerprints. In this work, we proposed SlidePass, a secure earables authentication system that leverages the finger-face acoustic friction produced by sliding finger gestures on the face. In particular, our system leverages the inward-facing microphone of the earables to reliably capture the acoustic of finger-face frictions. The core insight of our system is to utilize the face as a natural scanner for finger-face friction and earables to capture and reconstruct the fingerprint features. SlidePass is specially designed for earables. Due to the finger-face friction captured and encrypted by the face channel that is unique and hidden in the human skull, SlidePass is more resistant to various spoofing attacks. Our preliminary evaluation included ten different fingerprints showing that SlidePass achieves an average accuracy of 94%.
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海报:基于指纹-面部摩擦的可听认证
可穿戴设备(earables)已成为各种应用的新兴和广泛接受的平台。由于可穿戴设备的输入接口有限,传统的身份验证方法越来越不受欢迎。然而,可穿戴设备丰富的传感能力和独特的人脸-耳通道为指纹的再利用带来了新的传感机会。在这项工作中,我们提出了SlidePass,这是一种安全的可穿戴设备认证系统,利用手指在面部滑动手势产生的手指-面部声学摩擦。特别是,我们的系统利用可穿戴设备的内面向麦克风来可靠地捕捉手指与面部摩擦的声音。该系统的核心思想是利用面部作为手指-面部摩擦的天然扫描仪和可穿戴设备来捕获和重建指纹特征。SlidePass是专门为耳机设计的。由于通过隐藏在人类头骨中的独特面部通道捕获和加密的手指-面部摩擦,SlidePass更能抵抗各种欺骗攻击。我们的初步评估包括10个不同的指纹,显示SlidePass的平均准确率达到94%。
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