Abstract
Spoofing attacks on biometric systems are one of the major impediments to their use for secure unattended applications. This paper explores features for face liveness detection based on tracking the gaze of the user. In the proposed approach, a visual stimulus is placed on the display screen, at apparently random locations, which the user is required to follow while their gaze is measured. This visual stimulus appears in such a way that it repeatedly directs the gaze of the user to specific positions on the screen. Features extracted from sets of collinear and colocated points are used to estimate the liveness of the user. Data are collected from genuine users tracking the stimulus with natural head/eye movements and impostors holding a photograph, looking through a 2D mask or replaying the video of a genuine user. The choice of stimulus and features are based on the assumption that natural head/eye coordination for directing gaze results in a greater accuracy and thus can be used to effectively differentiate between genuine and spoofing attempts. Tests are performed to assess the effectiveness of the system with these features in isolation as well as in combination with each other using score fusion techniques. The results from the experiments indicate the effectiveness of the proposed gaze-based features in detecting such presentation attacks.
Highlights
Despite the widespread adoption of biometric recognition systems in recent decades, there still remain vulnerabilities to increasingly sophisticated spoofing attacks that can undermine the trust in such systems
An impostor can present a fake biometric sample of a genuine user to a biometric recognition system to gain access to unauthorized data or premises. This type of spoofing is a direct attack on the sensor; the impostor does not require any prior knowledge about the internal operation of the biometric system
In the context of biometric counterspoofing, liveness detection refers to such situations where the attacker uses an artefact presented at the sensor to subvert the system
Summary
Despite the widespread adoption of biometric recognition systems in recent decades, there still remain vulnerabilities to increasingly sophisticated spoofing attacks that can undermine the trust in such systems. An impostor can present a fake biometric sample of a genuine user to a biometric recognition system to gain access to unauthorized data or premises This type of spoofing is a direct attack on the sensor ( known as ‘‘presentation attack’’); the impostor does not require any prior knowledge about the internal operation of the biometric system. Pattern Anal Applic (2018) 21:437–449 motion, smiles, eye blinks, etc Such techniques can be deceived by presenting a video of the genuine user to the face recognition system. The subtle differences between a photograph (or video) of an individual and the live person can be used to establish liveness of the presentation at the sensor Another potential source of liveness information could be the nature of user interactions with the system, which can be captured and analysed in real time.
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