Continuous Authentication (CA) approaches are attracting attention due to the explosion of available sensors from IoT devices such as smartphones. However, a critical privacy concern arises when CA data is outsourced. Data from motion sensors may reveal users’ private issues. Despite the need for CA in smartphones, no previous work has explored how to tackle this matter leveraging motion sensors in a privacy-preserving way. In this work, a mechanism dubbed SmartCAMPP is proposed to achieve CA based on gyroscope and accelerometer data. Format-preserving encryption techniques are applied to privately outsource them. Our results show the suitability of the proposed scheme, featuring $76.85\%$ of accuracy while taking 5.12 ms. of computation for authenticating each user. Interestingly, the use of cryptography does not lead to a significant impact as compared to a non-privacy-preserving mechanism.

由于智能手机等物联网设备中可用传感器的爆炸性增长，连续身份验证（CA）方法引起了人们的注意。但是，将CA数据外包时会出现严重的隐私问题。来自运动传感器的数据可能会揭示用户的私人问题。尽管智能手机中需要CA，但以前没有工作探索如何以保护隐私的方式利用运动传感器来解决此问题。在这项工作中，提出了一种称为SmartCAMPP的机制，以基于陀螺仪和加速度计数据来实现CA。保留格式的加密技术被应用于将其私有外包。我们的结果表明了该方案的适用性，其特点是$76.85％$耗时5.12毫秒。用于验证每个用户的计算。有趣的是，与非隐私保护机制相比，使用密码术不会产生重大影响。