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On the vulnerability of face verification systems to hill-climbing attacks
Type of publication: Journal paper
Citation: Galbally_PR_2009
Journal: Pattern Recognition
Year: 2009
Abstract: In this paper, we use a hill-climbing attack algorithm based on Bayesian adaption to test the vulnerability of two face recognition systems to indirect attacks. The attacking technique uses the scores provided by the matcher to adapt a global distribution computed from an independent set of users, to the local specificities of the client being attacked. The proposed attack is evaluated on an eigenface-based and a parts-based face verification system using the XM2VTS database. Experimental results demonstrate that the hill-climbing algorithm is very efficient and is able to bypass over 85% of the attacked accounts (for both face recognition systems). The security flaws of the analyzed systems are pointed out and possible countermeasures to avoid them are also proposed.
Keywords:
Projects Idiap
MOBIO
Authors Galbally, Javier
McCool, Chris
Fierrez, Julian
Marcel, Sébastien
Ortega-Garcia, Javier
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