IriTrack: Liveness Detection Using Irises Tracking for Preventing Face Spoofing Attacks
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ID: 283543
2018
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Abstract
Face liveness detection has become a widely used technique with a growing
importance in various authentication scenarios to withstand spoofing attacks.
Existing methods that perform liveness detection generally focus on designing
intelligent classifiers or customized hardware to differentiate between the
image or video samples of a real legitimate user and the imitated ones.
Although effective, they can be resource-consuming and detection results may be
sensitive to environmental changes. In this paper, we take iris movement as a
significant liveness sign and propose a simple and efficient liveness detection
system named IriTrack. Users are required to move their eyes along with a
randomly generated poly-line, and trajectories of irises are then used as
evidences for liveness detection. IriTrack allows checking liveness by using
data collected during user-device interactions. We implemented a prototype and
conducted extensive experiments to evaluate the performance of the proposed
system. The results show that IriTrack can fend against spoofing attacks with a
moderate and adjustable time overhead.
| Reference Key |
hu2018iritrack
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|---|---|
| Authors | Meng Shen; Zelin Liao; Liehuang Zhu; Rashid Mijumbi; Xiaojiang Du; Jiankun Hu |
| Journal | arXiv |
| Year | 2018 |
| DOI |
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