This dataset contains data from 84 participants, collected in two settings: in the lab, and at home.

The data collected at home consists of multiple sessions performed over several weeks. During those sessions, participants were asked to interact with their smartphones in different body postures and movements. The dataset includes sensor data such as accelerometer and gyroscope readings with timestamps.

The dataset provides a valuable resource for understanding the relationship between body posture, movements, and mobile authentication performance. It can be used by researchers to explore the impact of different body postures and movements on mobile device security, and to develop more effective mobile authentication methods. By sharing this dataset, we hope to contribute to the wider research community and promote further investigation into this important topic.

All data was collected using an iPhone XR. Each participant completed an average of 25 sessions. During each session, subjects were asked to perform simple tasks, such as reading, writing, and image comparison. At the end of each reading and image comparison task, they were asked 3-5 questions about the task. In each session, users were not required to perform the tasks in a specific body position.

Data was collected with the approval NYIT IRB approval.

The dataset used in our work can be downloaded from this link

Dataset SHA-256: 3bdb29e670e95c338a2c0d321da532d33c2df72e9fe6b5bfd691e207d8178eb8.

Last updated: September 12, 2024.

Terms

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