Preprocessing and Feature Selection for Improved Sensor Interoperability in Online Biometric Signature Verification

Tolosana, Rubén; Vera-Rodríguez, Rubén; Ortega‐Garcia, Javier; Fiérrez, Julián

doi:10.1109/access.2015.2431493

Cited by 71 publications

(44 citation statements)

References 28 publications

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“…Finally, some important conclusions can be extracted comparing the results obtained in this work to the results obtained in previous work [6]. The high technological evolution and the improvement of sensor quality together with our proposed approach for dealing with device interoperability lead to very competitive signature verification systems based on finger input over COTS smartphones.…”

Section: E-biosign Benchmarkmentioning

confidence: 52%

Benchmarking desktop and mobile handwriting across COTS devices: The e-BioSign biometric database

et al. 2017

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This paper describes the design, acquisition process and baseline evaluation of the new e-BioSign database, which includes dynamic signature and handwriting information. Data is acquired from 5 different COTS devices: three Wacom devices (STU-500, STU-530 and DTU-1031) specifically designed to capture dynamic signatures and handwriting, and two general purpose tablets (Samsung Galaxy Note 10.1 and Samsung ATIV 7). For the two Samsung tablets, data is collected using both pen stylus and also the finger in order to study the performance of signature verification in a mobile scenario. Data was collected in two sessions for 65 subjects, and includes dynamic information of the signature, the full name and alpha numeric sequences. Skilled forgeries were also performed for signatures and full names. We also report a benchmark evaluation based on e-BioSign for person verification under three different real scenarios: 1) intra-device, 2) inter-device, and 3) mixed writing-tool. We have experimented the proposed benchmark using the main existing approaches for signature verification: feature- and time functions-based. As a result, new insights into the problem of signature biometrics in sensor-interoperable scenarios have been obtained, namely: the importance of specific methods for dealing with device interoperability, and the necessity of a deeper analysis on signatures acquired using the finger as the writing tool. This e-BioSign public database allows the research community to: 1) further analyse and develop signature verification systems in realistic scenarios, and 2) investigate towards a better understanding of the nature of the human handwriting when captured using electronic COTS devices in realistic conditions.

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Section: E-biosign Benchmarkmentioning

confidence: 52%

Benchmarking desktop and mobile handwriting across COTS devices: The e-BioSign biometric database

et al. 2017

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“…This stage is similar than the proposed in previous works [2]. Several statistical data normalization techniques have been studied in order to compensate for geometric differences between devices.…”

Section: A Data Preprocessing Stagementioning

confidence: 97%

“…While signatures from a genuine user differ significantly (high intra-class variability), skilled forgeries could be similar to genuine signatures (low interclass variability). Together with this intrinsic variability of signatures, there are sources of extrinsic variability such as the device interoperability scenario which affect significantly the performance of the system as it can be seen in recent works [2]. Therefore, it is important to take into account this new device interoperability scenario due to the high deployment of devices such as smartphones and tablets and their increasing popularity in our society.…”

Section: Introductionmentioning

confidence: 99%

Increasing the robustness of biometric templates for dynamic signature biometric systems

Tolosana

Vera-Rodríguez

Ortega‐Garcia

et al. 2015

2015 International Carnahan Conference on Security Technology (ICCST)

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El acceso a la versión del editor puede requerir la suscripción del recurso Access to the published version may require subscription Abstract-Due 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.

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“…While developing the MFA system, biometrics independence should be considered carefully, i.e., assurance of interoperability criteria should be met [170]. The framework needs to have functionality to handle the biometric data from sensors other than the initially deployed ones [171].…”

Section: Integrationmentioning

confidence: 99%

Multi-Factor Authentication: A Survey

et al. 2018

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Today, digitalization decisively penetrates all the sides of the modern society. One of the key enablers to maintain this process secure is authentication. It covers many different areas of a hyper-connected world, including online payments, communications, access right management, etc. This work sheds light on the evolution of authentication systems towards Multi-Factor Authentication (MFA) starting from Single-Factor Authentication (SFA) and through Two-Factor Authentication (2FA). Particularly, MFA is expected to be utilized for human-to-everything interactions by enabling fast, user-friendly, and reliable authentication when accessing a service. This paper surveys the already available and emerging sensors (factor providers) that allow for authenticating a user with the system directly or by involving the cloud. The corresponding challenges from the user as well as the service provider perspective are also reviewed. The MFA system based on reversed Lagrange polynomial within Shamir's Secret Sharing (SSS) scheme is further proposed to enable more flexible authentication. This solution covers the cases of authenticating the user even if some of the factors are mismatched or absent. Our framework allows for qualifying the missing factors by authenticating the user without disclosing sensitive biometric data to the verification entity. Finally, a vision of the future trends in MFA is discussed.

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Preprocessing and Feature Selection for Improved Sensor Interoperability in Online Biometric Signature Verification

Cited by 71 publications

References 28 publications

Benchmarking desktop and mobile handwriting across COTS devices: The e-BioSign biometric database

Benchmarking desktop and mobile handwriting across COTS devices: The e-BioSign biometric database

Increasing the robustness of biometric templates for dynamic signature biometric systems

Multi-Factor Authentication: A Survey

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