Abstract
One mode of authentication used in modern computing systems is graphical passwords. Graphical passwords are becoming more popular because touch-sensitive and pen-sensitive technologies are becoming ubiquitous. In this paper, we construct the “BioSketch” database, which is a general database of sketch-based passwords (SkPWs) with pressure information used as a biometric property. The BioSketch database is created so that recognition approaches may be commensurable with the benchmark performances. Using this database, we are also able to study the human-computer interaction (HCI) process for SkPWs. In this paper, we compare a generalized SKS recognition algorithm with the Fréchet distance in terms of the intra/inter-class variations and performances. The results show that the SKS-based approach achieves as much as a 7 % and 17 % reduction in equal error rate (EER) for random and skilled forgeries respectively.
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Notes
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- 2.
Resistive touchscreens cannot measure pressure.
- 3.
The distance is with respect to \(x_0\), which represents an arbitrary reference point (usually the centroid).
- 4.
SKS may be more robust than the Fréchet distance because it has broad definition of similar and a more narrow definition of different.
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Acknowledgements
The information in this paper is based on work partially funded by the United States Army Research Office (ARO) grant W911NF-04-D-0003-0019.
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Riggan, B.S., Snyder, W.E., Wang, X., Feng, J. (2014). A Human Factors Study of Graphical Passwords Using Biometrics. In: Jiang, X., Hornegger, J., Koch, R. (eds) Pattern Recognition. GCPR 2014. Lecture Notes in Computer Science(), vol 8753. Springer, Cham. https://doi.org/10.1007/978-3-319-11752-2_38
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