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A chimerical dataset combining physiological and behavioral biometric traits for reliable user authentication on
Sandeep Gupta1, Attaullah Buriro1, Bruno Crispo1,2
1Department of Information Engineering & Computer Science (DISI), University of Trento, Italy.
Abstract:
We present a chimerical dataset that combines both physiological and behavioral biometric traits, for reliable user authentication on smart devices and ecosystems [1]. The data are composed of statistical features computed from swipe-gesture, voice-prints, and face-images. The swipe and voice-prints data presented hereinafter are collected using a customized Android application - DriverAuth, however, the face data is obtained from the MOBIO Dataset [2]. We collected 10,320 swipe and voice-prints samples from 86 users worldwide by collaborating with a professional crowd-sourcing platform and formed a chimerical dataset adjunct to the publicly available MOBIO dataset with our collected dataset. The dataset consists of various statistical features computed from the raw data for all three traits, i.e., swipe, voice-print, and face.
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