Abstract
With the rapid development of mobile devices and the fast increase of sensitive data, secure and convenient mobile authentication technologies are desired. Except for traditional passwords, many mobile devices have biometric-based authentication methods (e.g., fingerprint, voiceprint, and face recognition), but they are vulnerable to spoofing attacks. To solve this problem, we study new biometric features which are based on the dental occlusion and find that the bone-conducted sound of dental occlusion collected in binaural canals contains unique features of individual bones and teeth. Motivated by this, we propose a novel authentication system, TeethPass+, which uses earbuds to collect occlusal sounds in binaural canals to achieve authentication. First, we design an event detection method based on spectrum variance to detect bone-conducted sounds. Then, we analyze the time-frequency domain of the sounds to filter out motion noises and extract unique features of users from four aspects: teeth structure, bone structure, occlusal location, and occlusal sound. Finally, we train a Triplet network to construct the user template, which is used to complete authentication. Through extensive experiments including 53 volunteers, the performance of TeethPass+ in different environments is verified. TeethPass+ achieves an accuracy of 98.6% and resists 99.7% of spoofing attacks.
Abstract (translated)
随着移动设备的快速发展和敏感数据量的快速增加，安全且便捷的移动认证技术变得越来越重要。除了传统的密码之外，许多移动设备还采用了基于生物特征的身份验证方法（例如指纹、声纹以及面部识别），但这些方法容易受到伪装攻击。为了解决这个问题，我们研究了一种新的生物特征——牙齿咬合，并发现双耳通道中采集到的由牙齿咬合产生的骨传导声音包含个体骨骼和牙齿的独特信息。基于这一发现，我们提出了一种新型认证系统TeethPass+，它利用耳机在双耳通道内收集牙齿咬合的声音来实现身份验证。 首先，我们设计了一种基于频谱变化的事件检测方法，用于识别骨传导的声音。然后，我们分析声音的时间-频率特性以过滤运动噪声，并从四个方面提取用户的独特特征：牙齿结构、骨骼结构、咬合位置和咬合声音。最后，我们训练了一个三元组网络来构建用户模板，该模板被用来完成认证过程。 通过包括53名志愿者在内的广泛实验验证了TeethPass+在不同环境下的性能表现。结果显示，TeethPass+的准确率为98.6%，并且能够抵御高达99.7%的伪装攻击。
URL
https://arxiv.org/abs/2504.00435
