BioTouchPass: Handwritten Passwords for Touchscreen Biometrics

This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessibleThis work enhances traditional authentication systems based on Personal Identification Numbers (PIN) and One- Time Passwords (OTP) through the incorporation of biometric information as a second level of user authentication. In our proposed approach, users draw each digit of the password on the touchscreen of the device instead of typing them as usual. A complete analysis of our proposed biometric system is carried out regarding the discriminative power of each handwritten digit and the robustness when increasing the length of the password and the number of enrolment samples. The new e-BioDigit database, which comprises on-line handwritten digits from 0 to 9, has been acquired using the finger as input on a mobile device. This database is used in the experiments reported in this work and it is available together with benchmark results in GitHub1. Finally, we discuss specific details for the deployment of our proposed approach on current PIN and OTP systems, achieving results with Equal Error Rates (EERs) ca. 4.0% when the attacker knows the password. These results encourage the deployment of our proposed approach in comparison to traditional PIN and OTP systems where the attack would have 100% success rate under the same impostor scenarioThis work has been supported by projects: BIBECA (MINECO), Bio-Guard (Ayudas Fundación BBVA a Equipos de Investigación Científica 2017) and by UAM-CecaBank. Ruben Tolosana is supported by a FPU Fellowship from Spanish MEC

Fusion of facial regions using color information in a forensic scenario

Comunicación presentada en: 18th Iberoamerican Congress on Pattern Recognition, CIARP 2013; Havana; Cuba; 20-23 November 2013The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-41827-3_50This paper reports an analysis of the benefits of using color information on a region-based face recognition system. Three different color spaces are analysed (RGB, YCbCr, lαβ) in a very challenging scenario matching good quality mugshot images against video surveillance images. This scenario is of special interest for forensics, where examiners carry out a comparison of two face images using the global information of the faces, but paying special attention to each individual facial region (eyes, nose, mouth, etc.). This work analyses the discriminative power of 15 facial regions comparing both the grayscale and color information. Results show a significant improvement of performance when fusing several regions of the face compared to just using the whole face image. A further improvement of performance is achieved when color information is consideredThis work has been partially supported by contract with Spanish Guardia Civil and projects BBfor2 (FP7-ITN-238803), bio-Challenge (TEC2009-11186), Bio Shield (TEC2012-34881), Contexts (S2009/TIC-1485), TeraSense (CSD2008-00068) and "Cátedra UAM-Telefónica

Preprocessing and feature selection for improved sensor interoperability in online biometric signature verification

Under a IEEE Open Access Publishing Agreement.Due to the technological evolution and the increasing popularity of smartphones, people can access an application using authentication based on biometric approaches from many different devices. Device interoperability is a very challenging problem for biometrics, which needs to be further studied. In this paper, we focus on interoperability device compensation for online signature verification since this biometric trait is gaining a significant interest in banking and commercial sector in the last years. The proposed approach is based on two main stages. The first one is a preprocessing stage where data acquired from different devices are processed in order to normalize the signals in similar ranges. The second one is based on feature selection taking into account the device interoperability case, in order to select to select features which are robust in these conditions. This proposed approach has been successfully applied in a similar way to two common system approaches in online signature verification, i.e., a global features-based system and a time functions-based system. Experiments are carried out using Biosecure DS2 (Wacom device) and DS3 (Personal Digital Assistant mobile device) dynamic signature data sets which take into account multisession and two different scenarios emulating real operation conditions. The performance of the proposed global features-based and time functions-based systems applying the two main stages considered in this paper have provided an average relative improvement of performance of 60.3% and 26.5% Equal Error Rate (EER), respectively, for random forgeries cases, compared with baseline systems. Finally, a fusion of the proposed systems has achieved a further significant improvement for the device interoperability problem, especially for skilled forgeries. In this case, the proposed fusion system has achieved an average relative improvement of 27.7% EER compared with the best performance of time functions-based system. These results prove the robustness of the proposed approach and open the door for future works using devices as smartphones or tablets, commonly used nowadays.This work was supported in part by the Project Bio-Shield under Grant TEC2012-34881, in part by Cecabank e-BioFirma Contract, and in part by Catedra UAM-Telefonic

Increasing the Robustness of Biometric Templates for Dynamic Signature Biometric Systems

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. R. Tolosana, R. Vera-Rodriguez, J. Ortega-Garcia and J. Fierrez, "Increasing the robustness of biometric templates for dynamic signature biometric systems," Security Technology (ICCST), 2015 International Carnahan Conference on, Taipei, 2015, pp. 229-234. doi: 10.1109/CCST.2015.7389687Due to the high deployment of devices such as smartphones and tablets and their increasing popularity in our society, the use of biometric traits in commercial and banking applications through these novel devices as an easy, quick and reliable way to perform payments is rapidly increasing. The handwritten signature is one of the most socially accepted biometric traits in these sectors due to the fact that it has been used in financial and legal transitions for centuries. In this paper we focus on dynamic signature verification systems. Nowadays, most of the state-of-the-art systems are based on extracting information contained in the X and Y spatial position coordinates of the signing process, which is stored in the biometric templates. However, it is critical to protect this sensible information of the users signatures against possible external attacks that would allow criminals to perform direct attacks to a biometric system or carry out high quality forgeries of the users signatures. Following this problem, the goal of this work is to study the performance of the system in two cases: first, an optimal time functions-based system taking into account the information related to X and Y coordinates and pressure, which is the common practice (i.e. Standard System). Second, we study an extreme case not considering information related to X, Y coordinates and their derivatives on the biometric system (i.e. Secure System), which would be a much more robust system against attacks, as this critical information would not be stored anywhere. The experimental work is carried out using e-BioSign database which makes use of 5 devices in total. The systems considered in this work are based on Dynamic Time Warping (DTW), an elastic measure over the selected time functions. Sequential Forward Features Selection (SFFS) is applied as a reliable way to obtain an optimal time functions vector over a development subset of users of the database. The results obtained over the evaluation subset of users of the database show a similar performance for both Standard and Secure Systems. Therefore, the use of a Secure System can be useful in some applications such as banking in order to avoid the lost of important user information against possible external attacks.This work was supported in part by the Project Bio-Shield (TEC2012-34881), in part by Cecabank e-BioFirma Contract, in part by the BEAT Project (FP7-SEC-284989) and in part by Catedra UAM-Telefonica

Update Strategies for HMM-Based Dynamic Signature Biometric Systems

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. [R. Tolosana, R. Vera-Rodriguez, J. Ortega-Garcia and J. Fierrez, "Update strategies for HMM-based dynamic signature biometric systems," Information Forensics and Security (WIFS), 2015 IEEE International Workshop on, Rome, 2015, pp. 1-6. doi: 10.1109/WIFS.2015.7368583Biometric authentication on devices such as smart- phones and tablets has increased significantly in the last years. One of the most acceptable and increasing traits is the handwrit- ing signature as it has been used in financial and legal agreements scenarios for over a century. Nowadays, it is frequent to sign in banking and commercial areas on digitizing tablets. For these reasons, it is necessary to consider a new scenario where the number of training signatures available to generate the user template is variable and besides it has to be taken into account the lap of time between them (inter-session variability). In this work we focus on dynamic signature verification. The main goal of this work is to study system configuration update strategies of time functions-based systems such as Hidden Markov Model (HMM) and Gaussian Mixture Models (GMM). Therefore, two different cases have been considered. First, the usual case of having an HMM-based system with a fixed configuration (i.e. Baseline System). Second, an HMM-based and GMM-based sys- tems whose configurations are optimized regarding the number of training signatures available to generate the user template. The experimental work has been carried out using an extended version of the Signature Long-Term database taking into account skilled and random or zero-effort forgeries. This database is comprised of a total of 6 different sessions distributed in a 15-month time span. Analyzing the results, the Proposed Systems achieve an average absolute improvement of 4.6% in terms of EER(%) for skilled forgeries cases compared to the Baseline System whereas the average absolute improvement for the random forgeries cases is of 2.7% EER. These results show the importance of optimizing the configuration of the systems compared to a fixed configuration system when the number of training signatures available to generate the user template increases.This work was supported in part by the Project Bio-Shield (TEC2012-34881), in part by Cecabank e-BioFirma Contract, in part by the BEAT Project (FP7-SEC-284989) and in part by Catedra UAM-Telefonica

BehavePassDB: Public Database for Mobile Behavioral Biometrics and Benchmark Evaluation

Mobile behavioral biometrics have become a popular topic of research, reaching promising results in terms of authentication, exploiting a multimodal combination of touchscreen and background sensor data. However, there is no way of knowing whether state-of-the-art classifiers in the literature can distinguish between the notion of user and device. In this article, we present a new database, BehavePassDB, structured into separate acquisition sessions and tasks to mimic the most common aspects of mobile Human-Computer Interaction (HCI). BehavePassDB is acquired through a dedicated mobile app installed on the subjects devices, also including the case of different users on the same device for evaluation. We propose a standard experimental protocol and benchmark for the research community to perform a fair comparison of novel approaches with the state of the art1. We propose and evaluate a system based on Long-Short Term Memory (LSTM) architecture with triplet loss and modality fusion at score levelThis project has received funding from the European Unions Horizon 2020 research and innovation programme under the Marie Skodowska-Curie grant agreement no. 860315, and from Orange Labs. R. Tolosana and R. Vera-Rodriguez are also supported by INTER-ACTION (PID2021-126521OB-I00 MICINN/FEDER

e-BioSign Tool: Towards Scientific Assessment of Dynamic Signatures under Forensic Conditions

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. R. Vera-Rodriguez, J. Fierrez, J. Ortega-Garcia, A. Acien and R. Tolosana, "e-BioSign tool: Towards scientific assessment of dynamic signatures under forensic conditions," 2015 IEEE 7th International Conference on Biometrics Theory, Applications and Systems (BTAS), Arlington, VA, 2015, pp. 1-6. doi: 10.1109/BTAS.2015.7358756This paper presents a new tool specifically designed to carry out dynamic signature forensic analysis and give sci- entific support to forensic handwriting examiners (FHEs). Traditionally FHEs have performed forensic analysis of paper-based signatures for court cases, but with the rapid evolution of the technology, nowadays they are being asked to carry out analysis based on signatures acquired by digi- tizing tablets more and more often. In some cases, an option followed has been to obtain a paper impression of these sig- natures and carry out a traditional analysis, but there are many deficiencies in this approach regarding the low spa- tial resolution of some devices compared to original off-line signatures and also the fact that the dynamic information, which has been proved to be very discriminative by the bio- metric community, is lost and not taken into account at all. The tool we present in this paper allows the FHEs to carry out a forensic analysis taking into account both the tra- ditional off-line information normally used in paper-based signature analysis, and also the dynamic information of the signatures. Additionally, the tool incorporates two impor- tant functionalities, the first is the provision of statistical support to the analysis by including population statistics for genuine and forged signatures for some selected features, and the second is the incorporation of an automatic dy- namic signature matcher, from which a likelihood ratio (LR) can be obtained from the matching comparison between the known and questioned signatures under analysis.This work was supported in part by the Project Bio-Shield (TEC2012-34881), in part by Cecabank e-BioFirma Contract, in part by the BEAT Project (FP7-SEC-284989) and in part by Catedra UAM-Telefonica

Simulation of millimeter-wave body images and its application to biometric recognition

Miriam Moreno-Moreno ; Julian Fierrez ; Ruben Vera-Rodriguez ; Josep Parron; "Simulation of millimeter-wave body images and its application to biometric recognition", Passive and Active Millimeter-Wave Imaging XV, Proc. SPIE 8362 (May 1, 2012); doi:10.1117/12.918549. Copyright 2012 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 Passive and Active Millimeter-Wave Imaging XV (Baltimore, Maryland, USA)One of the emerging applications of the millimeter-wave imaging technology is its use in biometric recognition. This is mainly due to some properties of the millimeter-waves such as their ability to penetrate through clothing and other occlusions, their low obtrusiveness when collecting the image and the fact that they are harmless to health. In this work we first describe the generation of a database comprising 1200 synthetic images at 94 GHz obtained from the body of 50 people. Then we extract a small set of distance-based features from each image and select the best feature subsets for person recognition using the SFFS feature selection algorithm. Finally these features are used in body geometry authentication obtaining promising results.This work has been partially supported by projects Bio-Challenge (TEC2009-11186), Contexts (S2009/TIC-1485), TeraSense (CSD2008-00068) and “Cátedra UAM-Telefónica”

Facial soft biometric features for forensic face recognition

This is the author’s version of a work that was accepted for publication in Forensic Science International. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Forensic Science International, VOL 257, (2015) DOI 10.1016/j.forsciint.2015.09.002This paper proposes a functional feature-based approach useful for real forensic caseworks, based on the shape, orientation and size of facial traits, which can be considered as a soft biometric approach. The motivation of this work is to provide a set of facial features, which can be understood by non-experts such as judges and support the work of forensic examiners who, in practice, carry out a thorough manual comparison of face images paying special attention to the similarities and differences in shape and size of various facial traits. This new approach constitutes a tool that automatically converts a set of facial landmarks to a set of features (shape and size) corresponding to facial regions of forensic value. These features are furthermore evaluated in a population to generate statistics to support forensic examiners. The proposed features can also be used as additional information that can improve the performance of traditional face recognition systems. These features follow the forensic methodology and are obtained in a continuous and discrete manner from raw images. A statistical analysis is also carried out to study the stability, discrimination power and correlation of the proposed facial features on two realistic databases: MORPH and ATVS Forensic DB. Finally, the performance of both continuous and discrete features is analyzed using different similarity measures. Experimental results show high discrimination power and good recognition performance, especially for continuous features. A final fusion of the best systems configurations achieves rank 10 match results of 100% for ATVS database and 75% for MORPH database demonstrating the benefits of using this information in practice.This work has been partially supported by Spanish Guardia Civil, projects Bio-Shield (TEC2012-34881) from Spanish MINECO and BEAT (FP7-SEC-284989) from EU, and Catedra UAM Telefonica

Identification using face regions: Application and assessment in forensic scenarios

This is the author’s version of a work that was accepted for publication in Forensic Science International. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Forensic Science International, 23, 1-3, (2013) DOI: 10.1016/j.forsciint.2013.08.020This paper reports an exhaustive analysis of the discriminative power of the different regions of the human face on various forensic scenarios. In practice, when forensic examiners compare two face images, they focus their attention not only on the overall similarity of the two faces. They carry out an exhaustive morphological comparison region by region (e.g., nose, mouth, eyebrows, etc.). In this scenario it is very important to know based on scientific methods to what extent each facial region can help in identifying a person. This knowledge obtained using quantitative and statical methods on given populations can then be used by the examiner to support or tune his observations. In order to generate such scientific knowledge useful for the expert, several methodologies are compared, such as manual and automatic facial landmarks extraction, different facial regions extractors, and various distances between the subject and the acquisition camera. Also, three scenarios of interest for forensics are considered comparing mugshot and Closed-Circuit TeleVision (CCTV) face images using MORPH and SCface databases. One of the findings is that depending of the acquisition distances, the discriminative power of the facial regions change, having in some cases better performance than the full face