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The vulnerabilities of fingerprint-based recognition systems to direct attacks with and without the cooperation of the user are studied. Two different systems, one minutiae-based and one ridge feature-based, are evaluated on a database of real and fake fingerprints. Based on the fingerprint images quality and on the results achieved on different operational scenarios, we obtain a number of statistically significant observations regarding the robustness of the systems., Comment: Published at Springer Journal of Telecommunication Systems, Special Issue of Biometrics Systems & Applications

Due to the fact that biometrics, as an automatic means of human recognition, constitutes a relatively novel field of research (Jain et al., 2006), to date most efforts undertaken by the different parties involved in the development of this technology (researchers, industry, evaluators, etc.) have been mainly focused on the improvement of its performance (i.e. finding novel methods to obtain lower error rates) (Wayman et al., 2005; Cappelli et al., 2006). As a consequence, other important aspects closely related to this type of system such as the performance degradation effect known as ageing have been left partially uncovered (Jain et al., 2008).

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. Martinez-Diaz, M.; Fierrez, J. ; Galbally, J. "The DooDB Graphical Password Database: Data Analysis and Benchmark Results" IEEE Access, vol. 1 pp. 596 - 605, 2013, We present DooDB, a doodle database containing data from 100 users captured with a touch screen-enabled mobile device under realistic conditions following a systematic protocol. The database contains two corpora: 1) doodles and 2) pseudo-signatures, which are simplified finger-drawn versions of the handwritten signature. The dataset includes genuine samples and forgeries, produced under worst-case conditions, where attackers have visual access to the drawing process. Statistical and qualitative analyses of the data are presented, comparing doodles and pseudo-signatures to handwritten signatures. Time variability, learning curves, and discriminative power of different features are also studied. Verification performance against forgeries is analyzed using state-of-the-art algorithms and benchmark results are provided., This work was supported by projects Contexts under Grant S2009/TIC-1485 from CAM, Bio-Challenge under Grant TEC2009-11186 and Bio-Shield under Grant TEC2012-34881 from Spanish MECD, and BEAT under Grant FP7-SEC-284989 from EU

This work is focused on dynamic signature verification for state-of-the-art smart phones, including performance evaluation. The analysis was performed on database consisting of 25 users and 500 signatures in total acquired with Samsung Galaxy Note. The verification algorithm tested combines two approaches: feature based (using Mahalanobis distance) and function based (using DTW), and the results are shown in terms of EER values. A number of experimental findings associated with signature verification in this scenario are obtained, e.g., the dominant challenge associated with the intra-class variability across time. As a result of the algorithm adaptation to the mobile scenario, the use of a state-of-the-art smart phone, and contrarily to what has been evidenced in previous works, we finally demonstrate that signature verification on smart phones can result in a similar verification performance compared to one obtained using more ergonomic stylus-based pen tablets. In particular, the best result achieved is an EER of 0.525%.

In semiconductor manufacturing, the early detection of defects is one of the key factors to increase the yield. In this paper, we present an optical sensor for the detection of photo resist failures which has been integrated into the spin coating process equipment. The detection method is based on the measurement of light which is scattered at imperfections of the photo resist layer. In the case of the detection of a photoresist failure, the sensor sets an alarm which is sent to the advanced process control (APC) system.

International audience; In this paper, we present the main results of the BioSecure Signature Evaluation Campaign (BSEC'2009). The objective of BSEC'2009 was to evaluate different online signature algorithms on two tasks: the first one aims at studying the influence of acquisition conditions (digitizing tablet or PDA) on systems' performance; the second one aims at studying the impact of information content in signatures on systems' performance. In BSEC'2009, the two BioSecure Data Sets DS2 and DS3 are used for tests, both containing data of the same 382 people, acquired respectively on a digitizing tablet and on a PDA. The results of the 12 systems involved in this evaluation campaign are reported and analyzed in detail in this paper. Experimental results reveal a 2.2% EER for skilled forgeries and a 0.51% EER for random forgeries on DS2; and a 4.97% EER for skilled forgeries and a 0.55% EER for random forgeries on DS3.

An analysis of the quality of on-line handwritten signatures is carried out based on the Sigma-Lognormal model. In the study, two main issues are addressed from a kinematic perspective of humanly-produced movements. On the one hand, what makes some signatures perform better than others in automatic signature verification systems, and on the other hand if that information may be used as a quality measure in order to predict the expected performance of a given sample. Experiments were carried out on the MCYT database and show the high potential of certain kinematic features for signature quality assessment.

Doodle-based graphical passwords represent a challenging scenario due to their high variability and the tendency to be graphically simple. Despite this, doodle-based authentication using touch screens is a promising lightweight user verification method. Several works have been published in this field, although they report in general experimental verification results over small and private databases. In this paper we analyze the performance of several state-of-the-art systems for doodle verification, using the recently acquired DooDB database, which is publicly available. Several algorithms are tested, from the fields of gesture recognition and doodle and signature verification. A comparative study of their performance is done, and future research directions are pointed out.

The kinematical information present in synthetically generated signatures is analyzed using the Sigma-Lognormal model and compared to the kinematical properties of real samples. Experiments are carried out on totally independent development and test sets and show a high degree of similarity between humanly produced and artificial signatures. One particular flaw is found in the velocity profile of synthetic signatures. Two possible solutions are proposed to improve the synthetic generation method using the Kinematic Theory of rapid human movements.

Automatic signature verification on handheld devices can be seen as a means to improve usability in consumer applications and a way to reduce costs in corporate environments. It can be easily integrated in touchscreen devices, for example, as a part of combined handwriting and keypad-based multimodal interfaces. In the last few decades, several approaches to the problem of signature verification have been proposed. However, most research has been carried out considering signatures captured with digitizing tables, in which the quality of the captured data is much higher than in handheld devices. Signature verification on handheld devices represents a new scenario both for researchers and vendors. In this chapter, we introduce automatic signature verification as a component of multimodal interfaces; we analyze the applications and challenges of signature verification and overview available resources and research directions. A case study is also given, in which a state-of-the-art signature verification system adapted to handheld devices is presented.

Javier Galbally ; Julian Fierrez ; Marcos Martinez-Diaz ; Javier Ortega-Garcia; "Synthetic generation of handwritten signatures based on spectral analysis", Optics and Photonics in Global Homeland Security V and Biometric Technology for Human Identification VI, Proc. SPIE 7306 (May 05, 2009); doi:10.1117/12.817928. Copyright 2009 Society of Photo‑Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited., Proceedings of the V Optics and Photonics in Global Homeland Security; and VI Biometric Technology for Human Identification (Orlando, Florida, United States), A new method to generate synthetic online signatures is presented. The algorithm uses a parametrical model to generate the synthetic Discrete Fourier Transform (DFT) of the trajectory signals, which are then refined in the time domain and completed with a synthetic pressure function. Multiple samples of each signature are created so that synthetic databases may be produced. Quantitative and qualitative results are reported, showing that, in addition to presenting a very realistic appearance, the synthetically generated signatures have very similar characteristics to those that enable the recognition of real signatures., This work was supported by Spanish MEC under project TEC2006-13141-C03-03.

In the present contribution, the applicability of off-line handwritten signatures to the fuzzy vault construction is studied. Feature extraction is based on quantized maxima and minima from upper and lower envelopes of the signature. Baseline results are reported for skilled and random forgeries of the MCYT off-line signature database, showing that the proposed scheme is suitable for signers with good separability between genuine signatures and skilled forgeries.

The applicability of universal background models as a score normalization technique is studied for the case of dynamic signature verification. This technique is commonly used in speaker verification systems. Background models are tested in two different systems based on global features: one based on Parzen windows and another based on adapted Gaussian mixture models. Experiments are carried out in the large MCYT database (16,500 signatures from 330 users) revealing a significant improvement in the overall system performance, specially in the casual impostor scenario.

In this work, resampling techniques and interpolation are applied to on-line signatures. Their effect on the performance of an on-line signature system using hidden Markov models is studied. The presented techniques are based on linear interpolation and Catmull-Rom cubic splines. Experimental results are provided on the MCYT database comprising 16,500 signatures from 330 subjects and as many skilled forgeries. Our approach allows to reduce the sampling rate of the on-line signature capture system, leading to the reduction of storage resource requirements and increased simplicity without compromising and even enhancing the system performance. This also leads to the discussion of which is the minimum sampling rate for HMM-based dynamic signature verification.

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. M. Martínez-Díaz, J. Fiérrez-Aguilar, F. Alonso-Fernández, J. Ortega-García, J.A. Siguenza, "Hill-Climbing and Brute-Force Attacks on Biometric Systems: A Case Study in Match-on-Card Fingerprint Verification" in Proceedings of 40th Annual IEEE International Carnahan Conferences Security Technology ICCST, Lexington, KY (USA), 2006, 151 - 159, In this paper, we study the robustness of state-of-the-art automatic fingerprint verification systems against hill climbing and brute-force attacks. We compare the performance of this type of attacks against two different minutiae-based systems, the NIST Fingerprint Image Software 2 (NFIS2) reference system and a Match-on-Card based system. In order to study their success rate, the attacks are analyzed and modified in each scenario. We focus on the influence of initial conditions in hill-climbing attacks, like the number of minutiae in the synthetically generated templates or the performance of each type of modification in the template. We demonstrate how slight modifications in the hill-climbing algorithm lead to very different success rates, This work has been supported by the Spanish Ministry of Defense, BioSecure NoE and the TIC2003-08382-C05-01 project of the Spanish Ministry of Science and Technology

We study user interaction with touchscreens based on swipe gestures for personal authentication. This approach has been analyzed only recently in the last few years in a series of disconnected and limited works. We summarize those recent efforts and then compare them to three new systems ( based on support vector machine and Gaussian mixture model using selected features from the literature) exploiting independent processing of the swipes according to their orientation. For the analysis, four public databases consisting of touch data obtained from gestures sliding one finger on the screen are used. We first analyze the contents of the databases, observing various behavioral patterns, e.g., horizontal swipes are faster than vertical independently of the device orientation. We then explore an intra-session scenario, where users are enrolled and authenticated within the same day, and an inter-session one, where enrollment and test are performed on different days. The resulting benchmarks and processed data are made public, allowing the reproducibility of the key results obtained based on the provided score files and scripts. In addition to the remarkable performance, thanks to the proposed orientation-based conditional processing, the results show various new insights into the distinctiveness of swipe interaction, e.g., some gestures hold more user-discriminant information, data from landscape orientation is more stable, and horizontal gestures are more discriminative in general than vertical ones.