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Apple in my eyes (AIME): liveness detection for mobile security using corneal specular reflections

Published: 24 June 2021 Publication History

Abstract

In this paper, we present a novel software-based face Presentation Attack Detection (PAD) method named "Apple in My Eyes (AIME)" using screen display as a challenge and corneal specular reflections as a response for authenticating the liveness against presentation. To detect face liveness, AIME creates multiple image patterns on the authentication screen as a challenge, then captures meaningful corneal specular reflection responses from user's eyes using the front camera, and analyzes the reflective pattern images using various lightweight Machine Learning (ML) techniques under a subsecond level delay (200 ms). We demonstrate that AIME can detect various attacks, including digital images displayed on the phone or tablet, printed paper images, 2D paper masks, videos, 3D silicon masks, and 3D facial models using VR. AIME liveness detection can be applied for various contactless biometric authentication accurately and efficiently without any costly extra sensors.

References

[1]
Bc Martin Chrzan. 2014. Liveness detection for face recognition. Master's thesis (2014).
[2]
Stephanie Schuckers, Greg Cannon, Elham Tabassi, Meagan Karlsson, and Elaine Newton. 2019. FIDO Biometrics Requirements. Population 5 (2019), 2--1.

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  1. Apple in my eyes (AIME): liveness detection for mobile security using corneal specular reflections

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    cover image ACM Conferences
    MobiSys '21: Proceedings of the 19th Annual International Conference on Mobile Systems, Applications, and Services
    June 2021
    528 pages
    ISBN:9781450384438
    DOI:10.1145/3458864
    Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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    New York, NY, United States

    Publication History

    Published: 24 June 2021

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    Author Tags

    1. anti-spoofing
    2. liveness detection
    3. presentation attack detection

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    Acceptance Rates

    MobiSys '21 Paper Acceptance Rate 36 of 166 submissions, 22%;
    Overall Acceptance Rate 274 of 1,679 submissions, 16%

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    • Downloads (Last 12 months)16
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