In recent years, wearable technology is interwoven with our everyday lives because of its commoditization and comfort. Security and privacy become a big concern as many user-sensitive data have been stored in such devices, such as personal emails and bank accounts. Traditional user authentication techniques like PIN entry are unfriendly and vulnerable to shoulder surfing attacks. To address these problems, a number of new authentication methods have been proposed. In this survey, we review and categorize recent advances in user authentication for wearable devices. We classify existing studies into physiological biometrics based and behavioral biometrics based methods. For each category, we review how signal processing techniques have been used to extract features in various wearable devices. Leveraging these extracted features, specifically designed classification methods can be used to realize user authentication. Finally, we review evaluation metrics for user authentication in wearable devices. Overall, in this survey, we systematically study assorted state-of-the-art user authentication methods for wearable devices, aiming to provide guidance and directions for future research in this area.

近年来，可穿戴技术因其商品化和舒适性而与我们的日常生活交织在一起。安全和隐私成为一个大问题，因为许多用户敏感数据已存储在此类设备中，例如个人电子邮件和银行账户。PIN 输入等传统用户身份验证技术不友好，容易受到肩冲浪攻击。为了解决这些问题，已经提出了许多新的认证方法。在本次调查中，我们回顾并分类了可穿戴设备用户身份验证的最新进展。我们将现有研究分为基于生理生物特征的方法和基于行为生物特征的方法。对于每个类别，我们回顾了如何使用信号处理技术来提取各种可穿戴设备中的特征。利用这些提取的特征，可以使用专门设计的分类方法来实现用户认证。最后，我们回顾了可穿戴设备中用户身份验证的评估指标。总体而言，在本次调查中，我们系统地研究了可穿戴设备的各种最先进的用户身份验证方法，旨在为该领域的未来研究提供指导和方向。