User Authentication from Smartwatch Photoplethysmography sensor
首发时间:2021-03-29
Abstract:With the rapid proliferation of smartwatch, a secure and convenient smartwatch-based user authentication scheme are desired. As the widely deployed bioelectrical signal sensor in smartwatch, Photoplethysmography (PPG) sensors have shown potentials for authentication. Existing authentication solutions usually have some limitations. They require the user to provide an amount of registration data from user to reflect the profile of user, which may impact the experience of user. In this paper, we propose a PPG-based smartwatch authentication scheme. We leverage the Siamese Network to extract the feature of user from the PPG signal affected by the finger-level gesture for authentication. We conduct some experiments to evaluate the performance of the scheme. The experiment results show that our model has an average accuracy rate of 92.43\%. In addition, the authentication model can achieve high authentication accuracy with a small amount of user registration data.
keywords: User authentication, smartwatch, PPG sensor,siamese network
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基于智能手表PPG传感器的用户认证方案
摘要:随着智能手表的迅速普及,安全方便的用户认证方案成为人们的需要。作为被广泛部署在智能手表上的生物电信号传感器,PPG传感器展现了其在用户身份验证领域的潜力。现有的认证方案通常有一些限制,需要用户提供比较多的注册数据以充分地反映用户的身份特征,这可能会影响到用户的使用体验。本文提出了一种利用智能手表PPG传感器的用户认证方案。通过使用孪生网络从用户手指级手势的PPG信号中提取特征,对用户的身份进行认证。本文通过实验对方案的性能进行了评估,认证的平均准确率为92\%。此外,本文所提出的方案可以在少量的用户注册数据下实现较高的认证准确率。
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