Your Eyes Show What Your Eyes See (Y-EYES): Challenge-Response Anti-Spoofing Method for Mobile Security Using Corneal Specular Reflections

As the need for contactless biometric authentication becomes more significant during COVID-19, and beyond, the popular biometric authentication method for mobile devices, iris detection, and facial recognition confronts various usability, security, and privacy concerns, including mask-wearing and various Presentation Attacks (PA). Specifically, liveness detection against spoofed artifacts is one of the most challenging tasks as many existing methods cannot conclusively assess the user's physical presence in unsupervised environments. Even though several methods have been proposed for tackling PA with motion challenges and 3D mapping, most of them require expensive depth sensors and fail to detect sophisticated 3D reconstruction attacks. We present a software-based face PA Detection (PAD) method named "Your Eyes Show What Your Eyes See (Y-EYES),"which creates challenges and detects meaningful corneal specular reflection responses from human eyes. To detect human liveness, Y-EYES creates multiple screen image patterns as a challenge, then captures the response of corneal specular reflections using the front camera and analyzes the images using lightweight Machine Learning (ML) techniques. Y-EYES system components include challenge pattern generation, reflection image augmentation (e.g., super-resolution), and ML-based analyses. We have implemented Y-EYES as Android, iOS, and web apps. Our extensive experimental results show that Y-EYES achieves liveness detection with high accuracy at around 200 ms against various types of sophisticated PA. Y-EYES liveness detection can be applied for multiple contactless biometric authentications accurately and efficiently without any costly extra sensors.