Improving Gait Biometrics under Spoofing Attacks

Abstract

Abstract. Gait is a relatively new biometric modality which has a precious advantage over other modalities, such as iris and voice, in that it can be easily captured from a distance. While it has recently become a topic of great interest in biometric research, there has been little investigation into gait spoofing attacks where a person tries to imitate the clothing or walking style of someone else. We recently analysed for the first time the effects of spoofing attacks on silhouette based gait biometric systems and showed that it was indeed possible to spoof gait biometric systems by clothing impersonation and the deliberate selection of a target that has a similar build to the attacker. These findings are exploited in this current work for developing new solutions to cope with such possible spoofing attacks. We describe then in this paper an initial solution coping with gait spoofing attacks using part-based gait analysis. The proposed solution is thoroughly evaluated on the challenging USOU gait spoofing database collected within the EU Tabula Rasa project. The database consists of records of 22 subjects (14 male and 8 female), between 20-55 years old, walking through the Southampton tunnel in both their normal clothes and whilst wearing a common uniform. The obtained results are very promising and point out very interesting findings which can be used as a reference for developing more enhanced countermeasures by the research community.

Gait biometrics: investigating the use of the lower inner regions for people identification from landmark frames

“…This is because of the potential to overcome the limitations of major traditional and well established biometric solutions. This includes concealing biometric signature to spoofing attacks [7, 8]. There has been a large body of research on the use of gait biometrics into surveillance scenarios.…”

A Survey on Gait Recognition

“…Spoofing attacks on Video-based gait authentication. Hadid et al [165][166][167] showed successful impersonation of video-based gait biometrics. They suggested dividing the silhouette (and the body frame) into components and verifying each component separately.…”

Discrimination between Genuine and Cloned Gait Silhouette Videos via Autoencoder-Based Training Data Generation

“…They concluded that it is possible to spoof someone's silhouettes, unlike the conclusion of Gafurov's work. Thus, Hadid et al proposed an anti-spoofing method in their another work [19]. This method first divides a given silhouette into multiple horizontal portions and next computes Local Binary Patterns from Three Orthogonal Planes (LBP-TOP) for each portion, which are then concatenated into a single histogram vector.…”

“…In the past dozen years, a few studies have tackled the problem of spoofing attacks against gait recognition [18], [19]. However, their focus was not media clonebased spoofing but physical spoofing; that is, they only focused on the gait spoofing attack where an attacker physically tries to imitate clothes or walking style of a target person.…”