Improving gait biometrics under spoofing attacks

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.