ICISSP 2021 - Proceedings of the 7th International Conference on Information Systems Security and Privacy
In this paper, we consider the problem of authentication on a smartphone, based on gestures. Specifically, the gestures consist of users holding a smartphone while writing their initials in the air. Accelerometer data from 80 subjects was collected and we provide a preliminary analysis of this data using machine learning techniques. The machine learning techniques considered include principal component analysis (PCA) and support vector machines (SVM). The results presented here are intended to provide a baseline for additional research based on our dataset.
Accelerometer, Authentication, Gesture, Principal Component Analysis, Support Vector Machine
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This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Elliu Huang, Fabio Di Troia, Mark Stamp, and Preethi Sundaravaradhan. "A new dataset for smartphone gesture-based authentication" ICISSP 2021 - Proceedings of the 7th International Conference on Information Systems Security and Privacy (2021): 771-780. https://doi.org/10.5220/0010425807710780