Active user authentication for smartphones: A challenge data set and benchmark results

Upal Mahbub, Sayantan Sarkar, Vishal M. Patel, Rama Chellappa

Research output: Chapter in Book/Report/Conference proceedingConference contribution

99 Scopus citations

Abstract

In this paper, automated user verification techniques for smartphones are investigated. A unique non-commercial dataset, the University of Maryland Active Authentication Dataset 02 (UMDAA-02) for multi-modal user authentication research is introduced. This paper focuses on three sensors - front camera, touch sensor and location service while providing a general description for other modalities. Benchmark results for face detection, face verification, touch-based user identification and location-based next-place prediction are presented, which indicate that more robust methods fine-tuned to the mobile platform are needed to achieve satisfactory verification accuracy. The dataset will be made available to the research community for promoting additional research.

Original languageEnglish (US)
Title of host publication2016 IEEE 8th International Conference on Biometrics Theory, Applications and Systems, BTAS 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781467397339
DOIs
StatePublished - Dec 19 2016
Event8th IEEE International Conference on Biometrics Theory, Applications and Systems, BTAS 2016 - Niagara Falls, United States
Duration: Sep 6 2016Sep 9 2016

Publication series

Name2016 IEEE 8th International Conference on Biometrics Theory, Applications and Systems, BTAS 2016

Other

Other8th IEEE International Conference on Biometrics Theory, Applications and Systems, BTAS 2016
Country/TerritoryUnited States
CityNiagara Falls
Period9/6/169/9/16

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Biomedical Engineering
  • Computer Science Applications

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