Context-aware active authentication using smartphone accelerometer measurements

Abena Primo, Vir V. Phoha, Rajesh Kumar, Abdul Serwadda

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

68 Scopus citations

Abstract

While body movement patterns recorded by a smartphone accelerometer are now well understood to be discriminative enough to separate users, little work has been done to address the question of if or how the position in which the phone is held affects user authentication. In this work, we show through a combination of supervised learning methods and statistical tests, that there are certain users for whom exploitation of information of how a phone is held drastically improves classification performance. We propose a two-stage authentication framework that identifies the location of the phone before performing authentication, and show its benefits based on a dataset of 30 users. Our work represents a first step towards bridging the gap between accelerometer-based authentication systems analyzed from the context of a laboratory environment and a real accelerometer-based authentication system in the wild where phone positioning cannot be assumed.

Original languageEnglish
Title of host publicationProceedings - 2014 IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2014
PublisherIEEE Computer Society
Pages98-105
Number of pages8
ISBN (Electronic)9781479943098, 9781479943098
DOIs
StatePublished - Sep 24 2014
Event2014 IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2014 - Columbus, United States
Duration: Jun 23 2014Jun 28 2014

Publication series

NameIEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
ISSN (Print)2160-7508
ISSN (Electronic)2160-7516

Conference

Conference2014 IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2014
CountryUnited States
CityColumbus
Period06/23/1406/28/14

Keywords

  • accelerometers
  • authentication
  • context awareness
  • gait recognition

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