In the Internet-of-Things (IoT) era, user authentication is essential to ensure the security of connected devices and the customization of passive services. However, conventional knowledge-based and physiological biometric-based authentication systems (e.g., password, face recognition, and fingerprints) are susceptible to shoulder surfing attacks, smudge attacks, and heat attacks. The powerful sensing capabilities of IoT devices, including smartphones, wearables, robots, and autonomous vehicles enable continuous authentication (CA) based on behavioral biometrics. The artificial intelligence (AI) approaches hold significant promise in sifting through large volumes of heterogeneous biometrics data to offer unprecedented user authentication and user identification capabilities. In this survey article, we outline the nature of CA in IoT applications, highlight the key behavioral signals, and summarize the extant solutions from an AI perspective. Based on our systematic and comprehensive analysis, we discuss the challenges and promising future directions to guide the next generation of AI-based CA research.

中文翻译：

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物联网时代用于连续认证的行为生物特征识别：人工智能视角

在物联网（IoT）时代，用户身份验证对于确保连接设备的安全性和无源服务的定制至关重要。然而，传统的基于知识和基于生理生物特征的认证系统（例如密码，面部识别和指纹）容易受到肩膀冲浪攻击，污迹攻击和热攻击。IoT设备（包括智能手机，可穿戴设备，机器人和自动驾驶汽车）的强大传感功能可基于行为生物识别技术进行连续认证（CA）。人工智能（AI）方法在筛选大量异类生物特征数据方面具有巨大的前景，可提供前所未有的用户身份验证和用户识别功能。在本调查文章中，我们概述了物联网应用中CA的性质，突出显示关键行为信号，并从AI角度总结现有解决方案。基于我们的系统和全面分析，我们讨论了挑战和有前途的未来方向，以指导下一代基于AI的CA研究。