Gait biometrics under spoofing attacks: An experimental investigation

Abdenour Hadid, Mohammad Ghahramani, Vili Kellokumpu, Xiaoyi Feng, John Bustard, Mark Nixon

Research output: Contribution to journalArticleScientificpeer-review

4 Citations (Scopus)

Abstract

Gait is a relatively 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. Although 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 analyzed 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. To gain deeper insight into the performance of current gait biometric systems under spoofing attacks, we provide a thorough investigation on how clothing can be used to spoof a target and evaluate the performance of two state-of-the-art recognition methods on a gait spoofing database recorded at the University of Southampton. Furthermore, we describe and evaluate an initial solution coping with gait spoofing attacks. The obtained results are very promising and point out interesting findings which can be used for future investigations.

Original languageEnglish
Article number063022
JournalJournal of Electronic Imaging
Volume24
Issue number6
DOIs
Publication statusPublished - 1 Nov 2015
MoE publication typeNot Eligible

Keywords

  • antispoofing
  • biometrics
  • gait recognition
  • spoofing attacks
  • video analysis

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