2 research outputs found
Score Normalization for Keystroke Dynamics Biometrics
Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. A. Morales, E. Luna-Garcia, J. Fierrez and J. Ortega-Garcia, "Score normalization for keystroke dynamics biometrics," Security Technology (ICCST), 2015 International Carnahan Conference on, Taipei, 2015, pp. 223-228. doi: 10.1109/CCST.2015.7389686This paper analyzes score normalization for keystroke
dynamics authentication systems. Previous studies have shown
that the performance of behavioral biometric recognition systems
(e.g. voice and signature) can be largely improved with score
normalization and target-dependent techniques. The main
objective of this work is twofold: i) to analyze the effects of
different thresholding techniques in 4 different keystroke
dynamics recognition systems for real operational scenarios; and
ii) to improve the performance of keystroke dynamics on the
basis of target-dependent score normalization techniques. The
experiments included in this work are worked out over the
keystroke pattern of 114 users from two different publicly
available databases. The experiments show that there is large
room for improvements in keystroke dynamic systems. The
results suggest that score normalization techniques can be used to
improve the performance of keystroke dynamics systems in more
than 20%. These results encourage researchers to explore this
research line to further improve the performance of these
systems in real operational environments.A.M. is supported by a post-doctoral Juan de la Cierva contract by the Spanish MECD (JCI-2012-12357). This work has been partially supported by projects: Bio-Shield (TEC2012-34881) from Spanish MINECO, BEAT (FP7-SEC-284989) from EU, CECABANK and Cátedra UAM Telefónica