Gaussian Mixture Models for on-line signature verification
WBMA '03 Proceedings of the 2003 ACM SIGMM workshop on Biometrics methods and applications
Biometric User Authentication for IT Security: From Fundamentals to Handwriting (Advances in Information Security)
A test tool to support brute-force online and offline signature forgery tests on mobile devices
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 3 (ICME '03) - Volume 03
Generation and evaluation of brute-force signature forgeries
MRCS'06 Proceedings of the 2006 international conference on Multimedia Content Representation, Classification and Security
Combined handwriting and speech modalities for user authentication
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans - Special section: Best papers from the 2007 biometrics: Theory, applications, and systems (BTAS 07) conference
Pressure evaluation in on-line and off-line signatures
BioID_MultiComm'09 Proceedings of the 2009 joint COST 2101 and 2102 international conference on Biometric ID management and multimodal communication
Cancelable templates for sequence-based biometrics with application to on-line signature recognition
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans - Special issue on recent advances in biometrics
On measuring forgery quality in online signatures
Pattern Recognition
Synthetic on-line signature generation. Part I: Methodology and algorithms
Pattern Recognition
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We present in this paper a new forgery scenario for dynamic signature verification systems. In this scenario, we assume that the forger has got access to a static version of the genuine signature, is using a dedicated software to automatically recover dynamics of the signature and is using these regained signatures to break the verification system. We also show that automated procedures can be built to regain signature dynamics, making some simple assumptions on how signatures are performed. We finally report on the evaluation of these procedures on the MCYT-100 signature database on which regained versions of the signatures are generated. This set of regained signatures is used to evaluate the rejection performance of a baseline dynamic signature verification system. Results show that the regained forgeries generate much more false acceptation in comparison to the random and low-force forgeries available in the MCYT-100 database. These results clearly show that such kind of forgery attacks can potentially represent a critical security breach for signature verification systems.