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 herein after 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.

A chimerical dataset combining physiological and behavioral biometric traits for reliable user authentication on smart devices and ecosystems

Attaullah Buriro;
2020-01-01

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 herein after 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.
2020
28
File in questo prodotto:
File Dimensione Formato  
1-s2.0-S235234091931279X-main.pdf

accesso aperto

Tipologia: Versione dell'editore
Licenza: Dominio pubblico
Dimensione 412.73 kB
Formato Adobe PDF
412.73 kB Adobe PDF Visualizza/Apri

I documenti in ARCA sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10278/5056280
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact