A closer look tells more: A facial distortion based liveness detection for face authentication

Yan Li, Zilong Wang, Yingjiu Li, Robert Deng, Binbin Chen, Weizhi Meng, Hui Li

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

Face authentication is vulnerable to media-based virtual face forgery (MVFF) where adversaries display photos/videos or 3D virtual face models of victims to spoof face authentication systems. In this paper, we propose a liveness detection mechanism, called FaceCloseup, to protect the face authentication on mobile devices. FaceCloseup detects MVFF-based attacks by analyzing the distortion of face regions in a user's closeup facial videos captured by built-in camera on mobile device. It can detect MVFF-based attacks with an accuracy of 99.48%.

Original languageEnglish
Title of host publicationProceedings of the 2019 ACM Asia Conference on Computer and Communications Security
PublisherAssociation for Computing Machinery
Publication date2 Jul 2019
Pages241-246
ISBN (Electronic)9781450367523
DOIs
Publication statusPublished - 2 Jul 2019
Event2019 ACM Asia Conference on Computer and Communications Security, AsiaCCS 2019 - Auckland, New Zealand
Duration: 9 Jul 201912 Jul 2019

Conference

Conference2019 ACM Asia Conference on Computer and Communications Security, AsiaCCS 2019
CountryNew Zealand
CityAuckland
Period09/07/201912/07/2019
SponsorAssociation for Computing Machinery

Keywords

  • Face authentication
  • Liveness detection
  • Perspective distortion

Fingerprint Dive into the research topics of 'A closer look tells more: A facial distortion based liveness detection for face authentication'. Together they form a unique fingerprint.

Cite this