Authcode - Dataset

AuthCODE is a multi-device continuous authentication architecture that guarantees the privacy of users' sensitive data while provides good authentication performance thanks to an hybrid approach that combines the Mobile Edge Computing (MEC) and Cloud Computing paradigms. A Smart Office scenario where five users interact with their personal computers and smartphones have been used to generate the following five datasets and measure the AuthCODE performance..Dataset 1. Single-device behaviour profile obtained from the personal computer, comprising aggregated data about keyboard and mouse activity, as well as application usage statistics.Dataset 2. Single-device behaviour profile obtained from the mobile device, with application usage statistics.Dataset 3. Single-device behaviour profile with features computed from the sensors of the mobile device.Dataset 4. Multi-device behaviour profile combining the most relevant features of the mobile device and personal computer.Dataset 5. Multi-device behaviour profile generated from the active/inactive intervals of both devices. There are multiple sub-datasets regarding the window size utilised, from 1 hour to 24 hours.AuthCODE是一种多设备持续认证架构，其凭借融合移动边缘计算（Mobile Edge Computing, MEC）与云计算范式的混合方案，在保障用户敏感数据隐私的同时，实现了优异的认证性能。本研究选取一个智能办公场景，该场景中有五名用户分别使用个人电脑与智能手机进行交互，以此生成以下五个数据集并对AuthCODE的性能进行测试。数据集1：取自个人电脑的单设备行为画像，包含键盘与鼠标活动的聚合数据，以及应用使用统计信息。数据集2：取自移动设备的单设备行为画像，包含应用使用统计数据。数据集3：基于移动设备传感器提取特征的单设备行为画像。数据集4：融合移动设备与个人电脑关键特征的多设备行为画像。数据集5：基于两种设备的活跃/非活跃间隔生成的多设备行为画像。该数据集包含多个以窗口时长划分的子数据集，窗口时长覆盖1小时至24小时不等。