Biometrics and Electronic Signatures 

About: Biometrics and Electronic Signatures is an academic conference. The conference publishes majorly in the area(s): Biometrics & Computer science. Over the lifetime, 166 publications have been published by the conference receiving 1312 citations.

A reference architecture for biometric template protection based on pseudo identities

Abstract: Biometric authentication is often considered to enhance identity verification. The use of biometrics also introduces new challenges to protect the privacy of the subjects while at the same time increasing the security of a verification system. In this paper, a set of requirements is proposed for biometric processing techniques to safeguard privacy and security. From these requirements, a reference architecture is derived that outlines processes and interfaces of biometric template protection methods in a high-level, technology-neutral way.

Authentication framework for smart cards

Abstract: A smart card authentication framework may include a card application applet (CAA), an authentication policy applet (APA), and an authentication technology applet (ATA). The CAA may provide a protected service for a user. The APA may provide an authentication-technology-independent user validation service for the CAA. The ATA may provide a technology-specific authentication service. In one embodiment, the CAA provides a first external interface, the ATA provides a second external interface and a first internal interface, and the APA provides a second internal interface. The ATA may receive a host request for user authentication via the second external interface, and the ATA may process the authentication request without participation by the CAA. The CAA may communicate with the APA via the first internal interface to determine whether the user is currently validated. If so, the CAA may provide the protected service for the host via the first external interface.

Spoofing 2D face recognition systems with 3D masks

Abstract: Vulnerability to spoofing attacks is a serious drawback for many biometric systems. Among all biometric traits, face is the one that is exposed to the most serious threat, since it is exceptionally easy to access. The limited work on fraud detection capabilities for face mainly shapes around 2D attacks forged by displaying printed photos or replaying recorded videos on mobile devices. A significant portion of this work is based on the flatness of the facial surface in front of the sensor. In this study, we complicate the spoofing problem further by introducing the 3rd dimension and examine possible 3D attack instruments. A small database is constructed with six different types of 3D facial masks and experimented on to determine the right direction to study 3D attacks. Spoofing performance for each type of mask is assessed and analysed thoroughly using two Gabor-wavelet-based algorithms.

Classification of acceleration data for biometric gait recognition on mobile devices

Abstract: Ubiquitous mobile devices like smartphones and tablets are often not secured against unauthorized access as the users tend to not use passwords because of convenience reasons Therefore, this study proposes an alternative user authentication method for mobile devices based on gait biometrics The gait characteristics are captured using the built-in accelerometer of a smartphone Various features are extracted from the measured accelerations and utilized to train a support vector machine (SVM) Among the extracted features are the Meland Bark-frequency cepstral coefficients (MFCC, BFCC) which are commonly used in speech and speaker recognition and have not been used for gait recognition previously The proposed approach showed competitive recognition performance, yielding 59% FMR at 63% FNMR in a mixedday scenario

User survey on phone security and usage

Abstract: Mobile phones are widely used nowadays and during the last years developed from simple phones to small computers with an increasing number of features. These result in a wide variety of data stored on the devices which could be a high security risk in case of unauthorized access. A comprehensive user survey was conducted to get information about what data is really stored on the mobile devices, how it is currently protected and if biometric authentication methods could improve the current state. This paper states the results from about 550 users of mobile devices. The analysis revealed a very low securtiy level of the devices. This is partly due to a low security awareness of their owners and partly due to the low acceptance of the offered authentication method based on PIN. Further results like the experiences with mobile thefts and the willingness to use biometric authentication methods as alternative to PIN authentication are also stated.