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Graphical Password-Based User Authentication With Free-Form Doodles
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AI
DOI：10.1109/THMS.2015.2504101.png)
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Abstract
En 中文
User authentication using simple gestures is now common in portable devices. In this work, authentication with free-form sketches is studied. Verification systems using dynamic time warping and Gaussian mixture models are proposed, based on dynamic signature verification approaches. The most discriminant features are studied using the sequential forward floating selection algorithm. The effects of the time lapse between capture sessions and the impact of the training set size are also studied. Development and validation experiments are performed using the DooDB database, which contains passwords from 100 users captured on a smartphone touchscreen. Equal error rates between 3% and 8% are obtained against random forgeries and between 21% and 22% against skilled forgeries. High variability between capture sessions increases the error rates.
Keywords:
Dynamic time warping (DTW)
Gaussian mixture models (GMMs)
gesture recognition
graphical passwords
mobile security
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