Newness and distinctiveness is claimed in the features of ornamentation as shown inside the broken line circle in the accompanying representation.

Display screen or portion thereof with graphical user interface

Biometric recognition offers a reliable solution to the problem of user authentication in identity management systems. With the widespread deployment of biometric systems in various applications, there are increasing concerns about the security and privacy of biometric technology. Public acceptance of biometrics technology will depend on the ability of system designers to demonstrate that these systems are robust, have low error rates, and are tamper proof. We present a high-level categorization of the various vulnerabilities of a biometric system and discuss countermeasures that have been proposed to address these vulnerabilities. In particular, we focus on biometric template security which is an important issue because, unlike passwords and tokens, compromised biometric templates cannot be revoked and reissued. Protecting the template is a challenging task due to intrauser variability in the acquired biometric traits. We present an overview of various biometric template protection schemes and discuss their advantages and limitations in terms of security, revocability, and impact on matching accuracy. A template protection scheme with provable security and acceptable recognition performance has thus far remained elusive. Development of such a scheme is crucial as biometric systems are beginning to proliferate into the core physical and information infrastructure of our society.

/pdf/biometric-template-security-3nxd1k841h.pdf

Biometric template security

We investigate whether a classifier can continuously authenticate users based on the way they interact with the touchscreen of a smart phone. We propose a set of 30 behavioral touch features that can be extracted from raw touchscreen logs and demonstrate that different users populate distinct subspaces of this feature space. In a systematic experiment designed to test how this behavioral pattern exhibits consistency over time, we collected touch data from users interacting with a smart phone using basic navigation maneuvers, i.e., up-down and left-right scrolling. We propose a classification framework that learns the touch behavior of a user during an enrollment phase and is able to accept or reject the current user by monitoring interaction with the touch screen. The classifier achieves a median equal error rate of 0% for intrasession authentication, 2%-3% for intersession authentication, and below 4% when the authentication test was carried out one week after the enrollment phase. While our experimental findings disqualify this method as a standalone authentication mechanism for long-term authentication, it could be implemented as a means to extend screen-lock time or as a part of a multimodal biometric authentication system.

/pdf/touchalytics-on-the-applicability-of-touchscreen-input-as-a-3a6lvvm3fr.pdf

Touchalytics: On the Applicability of Touchscreen Input as a Behavioral Biometric for Continuous Authentication

Display screen or portion thereof with transitional graphical user interface

In order to direct and build an effective, secure mobile ecosystem, we must first understand user attitudes toward security and privacy for smartphones and how they may differ from attitudes toward more traditional computing systems. What are users' comfort levels in performing different tasks? How do users select applications? What are their overall perceptions of the platform? This understanding will help inform the design of more secure smartphones that will enable users to safely and confidently benefit from the potential and convenience offered by mobile platforms.To gain insight into user perceptions of smartphone security and installation habits, we conduct a user study involving 60 smartphone users. First, we interview users about their willingness to perform certain tasks on their smartphones to test the hypothesis that people currently avoid using their phones due to privacy and security concerns. Second, we analyze why and how they select applications, which provides information about how users decide to trust applications. Based on our findings, we present recommendations and opportunities for services that will help users safely and confidently use mobile applications and platforms.

/pdf/measuring-user-confidence-in-smartphone-security-and-privacy-3rsalj73rw.pdf

Measuring user confidence in smartphone security and privacy

Most existing computer and network systems authenticate a user only at the initial login session. This could be a critical security weakness, especially for high-security systems because it enables an impostor to access the system resources until the initial user logs out. This situation is encountered when the logged in user takes a short break without logging out or an impostor coerces the valid user to allow access to the system. To address this security flaw, we propose a continuous authentication scheme that continuously monitors and authenticates the logged in user. Previous methods for continuous authentication primarily used hard biometric traits, specifically fingerprint and face to continuously authenticate the initial logged in user. However, the use of these biometric traits is not only inconvenient to the user, but is also not always feasible due to the user's posture in front of the sensor. To mitigate this problem, we propose a new framework for continuous user authentication that primarily uses soft biometric traits (e.g., color of user's clothing and facial skin). The proposed framework automatically registers (enrolls) soft biometric traits every time the user logs in and fuses soft biometric matching with the conventional authentication schemes, namely password and face biometric. The proposed scheme has high tolerance to the user's posture in front of the computer system. Experimental results show the effectiveness of the proposed method for continuous user authentication.

/pdf/soft-biometric-traits-for-continuous-user-authentication-1frmpagjbw.pdf

Soft Biometric Traits for Continuous User Authentication

Conventional computer systems authenticate users only at the initial log-in session, which can be the cause of a critical
security flaw. To resolve this problem, systems need continuous user authentication methods that continuously monitor
and authenticate users based on some biometric trait(s). We propose a new method for continuous user authentication
based on a Webcam that monitors a logged in user's face and color of clothing. Our method can authenticate users
regardless of their posture in front of the workstation (laptop or PC). Previous methods for continuous user
authentication cannot authenticate users without biometric observation. To alleviate this requirement, our method uses
color information of users' clothing as an enrollment template in addition to their face information. The system cannot
pre-register the clothing color information because this information is not permanent. To deal with the problem, our
system automatically registers this information every time the user logs in and then fuses it with the conventional
(password) identification system. We report preliminary authentication results and future enhancements to the proposed
system.

/pdf/continuous-user-authentication-using-temporal-information-21wcha3bc9.pdf

Continuous user authentication using temporal information

Difference sphere: An approach to near light source estimation

One of the major challenges encountered by face recognition lies in the difficulty of handling arbitrary poses variations. While different approaches have been developed for face recognition across pose variations, many methods either require manual landmark annotations or assume the face poses to be known. These constraints prevent many face recognition systems from working automatically. In this paper, we propose a fully automatic method for multiview face recognition. We first build a 3D model from each frontal target face image, which is used to generate synthetic target face images. The pose of a query face image is also estimated using a multi-view face detector so that the synthetic target face images can be generated to resemble the pose variation of a query face image. Procrustes analysis is then applied to align the synthetic target images and the query image, and block based MLBP features are extracted for face matching. Experimental results on two public-domain databases (Color FERET and PubFig), and a Mobile face database collected using mobile phones show that the proposed approach outperforms two state-of-the-art face matchers (FaceVACS and MKD-SRC) in automatic multi-view face recognition. The proposed approach can also be easily extended to leverage existing face recognition systems for automatic multi-view face recognition.

/pdf/automatic-multi-view-face-recognition-via-3d-model-based-6f2e3od1lb.pdf

Automatic multi-view face recognition via 3D model based pose regularization

For personal authentication using biometric information, to allow for unfailing authentication without increasing verification time even for an authentication object that is not supported only by a minutia matching method, the present invention provides a biometric information authentication device comprising: a first verifying section for verifying first to-be-verified data against first registration data registered preliminarily using a minutia matching method; a second verifying section for verifying second to-be-verified data against second registration data registered preliminarily using a pattern matching method; and a determining section for comparing match degree, which is obtained as a result of verification by the first verifying section, with a first threshold value and a second threshold value to allow the second verifying section to perform verification in the case where the match degree is equal to or smaller than the first threshold value and equal to or larger than the second threshold value.

Biometric information authentication device, biometric information authentication method, and computer-readable recording medium with biometric information authentication program recorded thereon

Koichiro Niinuma

Papers

Soft Biometric Traits for Continuous User Authentication

Continuous user authentication using temporal information

Difference sphere: An approach to near light source estimation

Automatic multi-view face recognition via 3D model based pose regularization

Biometric information authentication device, biometric information authentication method, and computer-readable recording medium with biometric information authentication program recorded thereon