Jawthenticate: Microphone-free Speech-based Authentication using Jaw Motion and Facial Vibrations
Jawthenticate: Microphone-free Speech-based Authentication using Jaw Motion and Facial Vibrations
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DOI：
10.1145/3625687.3625813
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发表时间：
2023-11
期刊：
影响因子：
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通讯作者：
Tanmay Srivastava;Shijia Pan;Phuc Nguyen;Shubham Jain
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文献类型：
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作者：
Tanmay Srivastava;Shijia Pan;Phuc Nguyen;Shubham Jain
在本文中，我们提出了 Jawthenticate，这是一种耳戴式系统，可以在不使用麦克风的情况下使用可听或不可听的语音对用户进行身份验证。该系统可以克服传统基于语音的身份验证系统的缺点，例如在噪声条件下不可靠以及使用基于麦克风的重放攻击进行欺骗。 Jawthenticate 从下巴运动和相关的面部振动中得出独特的与语音相关的特征。这种功能组合使 Jawthenticate 能够抵御声音模仿以及基于摄像头的欺骗。我们使用这些特征为每个用户训练一个二类 SVM 分类器。我们的系统对于语音的内容和语言是不变的。在一项对 41 位使用不同母语的受试者进行的研究中，Jawthenticate 仅用 3 秒的语音数据就实现了 97.07% 的平衡准确率 (BAC)、97.75% 的真阳性率 (TPR) 和 96.4% 的真阴性率 (TNR)。
In this paper, we present Jawthenticate, an earable system that authenticates a user using audible or inaudible speech without using a microphone. This system can overcome the shortcomings of traditional voice-based authentication systems like unreliability in noisy conditions and spoofing using microphone-based replay attacks. Jawthenticate derives distinctive speech-related features from the jaw motion and associated facial vibrations. This combination of features makes Jawthenticate resilient to vocal imitations as well as camera-based spoofing. We use these features to train a two-class SVM classifier for each user. Our system is invariant to the content and language of speech. In a study conducted with 41 subjects, who speak different native languages, Jawthenticate achieves a Balanced Accuracy (BAC) of 97.07%, True Positive Rate (TPR) of 97.75%, and True Negative Rate (TNR) of 96.4% with just 3 seconds of speech data.