Low Cost and Usable Multimodal Biometric System Based on Keystroke Dynamics and 2D Face Recognition

Abstract

We propose in this paper a low cost multimodal biometric system combining keystroke dynamics and 2D face recognition. The objective of the proposed system is to be used while keeping in mind: good performances, acceptability, and espect of privacy. Different fusion methods have been used (min, max, mul, svm, weighted sum configured with genetic algorithms, and, genetic programming) on the scores of three keystroke dynamics algorithms and two 2D face recognition ones. This multimodal biometric system improves the recognition rate in comparison with each individual method. On a chimeric database composed of 100 individuals, the best keystroke dynamics method obtains an EER of 8.77%, the best face recognition one has an EER of 6.38%, while the best proposed fusion system provides an EER of 2.22%.