Demo of PassFrame: Generating image-based passwords from egocentric videos

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

1 Citation (Scopus)

Abstract

We demonstrate a personalized user authentication mechanism based on first-person-view videos. Our proposed algorithm forms temporary image-based authentication challenges which benefit a variety of purposes such as unlocking a mobile device or fallback authentication. First, representative frames are extracted from the egocentric videos. Then, they are split into distinguishable segments before repetitive scenes are discarded through a clustering procedure. We integrate eye tracking data to select informative sequences of video frames and suggest an alternative method based on image quality. For evaluation, we perform experiments in different settings including object-interaction activities and traveling contexts. We assessed the authentication scheme in the presence of an informed attacker and observed that the entry time is significantly higher than that of the legitimate user.

Original languageEnglish
Title of host publication2017 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2017
PublisherIEEE
Pages76-78
Number of pages3
ISBN (Electronic)9781509043385
DOIs
Publication statusPublished - 2 May 2017
MoE publication typeA4 Article in a conference publication
Event IEEE International Conference on Pervasive Computing and Communications Workshops - Kona, United States
Duration: 13 Mar 201717 Mar 2017

Conference

Conference IEEE International Conference on Pervasive Computing and Communications Workshops
Abbreviated titlePerCom Workshops
CountryUnited States
CityKona
Period13/03/201717/03/2017

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