Gaze Stability for Liveness Detection

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 is 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

Security and accuracy of fingerprint-based biometrics: A review

Biometric systems are increasingly replacing traditional password- and token-based authentication systems. Security and recognition accuracy are the two most important aspects to consider in designing a biometric system. In this paper, a comprehensive review is presented to shed light on the latest developments in the study of fingerprint-based biometrics covering these two aspects with a view to improving system security and recognition accuracy. Based on a thorough analysis and discussion, limitations of existing research work are outlined and suggestions for future work are provided. It is shown in the paper that researchers continue to face challenges in tackling the two most critical attacks to biometric systems, namely, attacks to the user interface and template databases. How to design proper countermeasures to thwart these attacks, thereby providing strong security and yet at the same time maintaining high recognition accuracy, is a hot research topic currently, as well as in the foreseeable future. Moreover, recognition accuracy under non-ideal conditions is more likely to be unsatisfactory and thus needs particular attention in biometric system design. Related challenges and current research trends are also outlined in this paper

Security and accuracy of fingerprint-based biometrics: A review

Biometric systems are increasingly replacing traditional password- and token-based authentication systems. Security and recognition accuracy are the two most important aspects to consider in designing a biometric system. In this paper, a comprehensive review is presented to shed light on the latest developments in the study of fingerprint-based biometrics covering these two aspects with a view to improving system security and recognition accuracy. Based on a thorough analysis and discussion, limitations of existing research work are outlined and suggestions for future work are provided. It is shown in the paper that researchers continue to face challenges in tackling the two most critical attacks to biometric systems, namely, attacks to the user interface and template databases. How to design proper countermeasures to thwart these attacks, thereby providing strong security and yet at the same time maintaining high recognition accuracy, is a hot research topic currently, as well as in the foreseeable future. Moreover, recognition accuracy under non-ideal conditions is more likely to be unsatisfactory and thus needs particular attention in biometric system design. Related challenges and current research trends are also outlined in this paper

ReSCon '11, Research Student Conference: Book of Abstracts

The fourth SED Research Student Conference (ReSCon2011) was hosted over three days, 20-22 June 2011, in the Hamilton Centre at Brunel University. The conference consisted of technical presentations, a poster session and social events. which focused on current research being conducted within the School of Engineering and Design by postgraduate research students from the School. The conference is held annually, and ReSCon plays a key role in contributing to research and innovations within the School

Biometric Presentation Attack Detection for Mobile Devices Using Gaze Information

Facial recognition systems are among the most widely deployed in biometric applications. However, such systems are vulnerable to presentation attacks (spoofing), where a person tries to disguise as someone else by mimicking their biometric data and thereby gaining access to the system. Significant research attention has been directed toward developing robust strategies for detecting such attacks and thus assuring the security of these systems in real-world applications. This thesis is focused on presentation attack detection for face recognition systems using a gaze tracking approach. The proposed challenge-response presentation attack detection system assesses the gaze of the user in response to a randomly moving stimulus on the screen. The user is required to track the moving stimulus with their gaze with natural head/eye movements. If the response is adequately similar to the challenge, the access attempt is seen as genuine. The attack scenarios considered in this work included the use of hand held displayed photos, 2D masks, and 3D masks. Due to the nature of the proposed challenge-response approaches for presentation attack detection, none of the existing public databases were appropriate and a new database has been collected. The Kent Gaze Dynamics Database (KGDD) consists of 2,400 sets of genuine and attack-based presentation attempts collected from 80 participants. The use of a mobile device were simulated on a desktop PC for two possible geometries corresponding to mobile phone and tablet devices. Three different types of challenge trajectories were used in this data collection exercise. A number of novel gaze-based features were explored to develop the presentation attack detection algorithm. Initial experiments using the KGDD provided an encouraging indication of the potential of the proposed system for attack detection. In order to explore the feasibility of the scheme on a real hand held device, another database, the Mobile KGDD (MKGDD), was collected from 30 participants using a single mobile device (Google Nexus 6), to test the proposed features. Comprehensive experimental analysis has been performed on the two collected databases for each of the proposed features. Performance evaluation results indicate that the proposed gaze-based features are effective in discriminating between genuine and presentation attack attempts

Vulnerabilities and attack protection in security systems based on biometric recognition

Tesis doctoral inédita. Universidad Autónoma de Madrid, Escuela Politécnica Superior, noviembre de 200