Fingerprint Recognition with Embedded Cameras on Mobile Phones
17 May 2011-pp 136-147
TL;DR: A first step towards a novel biometric authentication approach applying cell phone cameras capturing fingerprint images as biometric traits is proposed and shows a biometric performance with an Equal Error Rate of 4.5% by applying a commercial extractor/comparator and without any preproccesing on the images.
Abstract: Mobile phones with a camera function are capable of capturing image and processing tasks. Fingerprint recognition has been used in many different applications where high security is required. A first step towards a novel biometric authentication approach applying cell phone cameras capturing fingerprint images as biometric traits is proposed. The proposed method is evaluated using 1320 fingerprint images from each embedded capturing device. Fingerprints are collected by a Nokia N95 and a HTC Desire. The overall results of this approach show a biometric performance with an Equal Error Rate (EER) of 4.5% by applying a commercial extractor/comparator and without any preproccesing on the images.
Citations
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TL;DR: This paper surveys the development of existing biometric authentication techniques on mobile phones, particularly on touch-enabled devices, with reference to 11 biometric approaches and proposes a framework for establishing a reliable authentication mechanism through implementing a multimodal biometric user authentication in an appropriate way.
Abstract: Designing reliable user authentication on mobile phones is becoming an increasingly important task to protect users' private information and data. Since biometric approaches can provide many advantages over the traditional authentication methods, they have become a significant topic for both academia and industry. The major goal of biometric user authentication is to authenticate legitimate users and identify impostors based on physiological and behavioral characteristics. In this paper, we survey the development of existing biometric authentication techniques on mobile phones, particularly on touch-enabled devices, with reference to 11 biometric approaches (five physiological and six behavioral). We present a taxonomy of existing efforts regarding biometric authentication on mobile phones and analyze their feasibility of deployment on touch-enabled mobile phones. In addition, we systematically characterize a generic biometric authentication system with eight potential attack points and survey practical attacks and potential countermeasures on mobile phones. Moreover, we propose a framework for establishing a reliable authentication mechanism through implementing a multimodal biometric user authentication in an appropriate way. Experimental results are presented to validate this framework using touch dynamics, and the results show that multimodal biometrics can be deployed on touch-enabled phones to significantly reduce the false rates of a single biometric system. Finally, we identify challenges and open problems in this area and suggest that touch dynamics will become a mainstream aspect in designing future user authentication on mobile phones.
239Â citations
Cites methods from "Fingerprint Recognition with Embedd..."
...[65] proposed an approach of applying cell phone cameras to capturing fingerprint images and evaluated up to 1320 fingerprint images from some embedded capturing devices like Nokia N95....
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Posted Content•
TL;DR: This paper focuses on designing, implementing, and evaluating TouchIn, a two-factor authentication system on multi-touch mobile devices that allows the user to draw on arbitrary regions on the touchscreen without looking at it.
Abstract: Mobile authentication is indispensable for preventing unauthorized access to multi-touch mobile devices. Existing mobile authentication techniques are often cumbersome to use and also vulnerable to shoulder-surfing and smudge attacks. This paper focuses on designing, implementing, and evaluating TouchIn, a two-factor authentication system on multi-touch mobile devices. TouchIn works by letting a user draw on the touchscreen with one or multiple fingers to unlock his mobile device, and the user is authenticated based on the geometric properties of his drawn curves as well as his behavioral and physiological characteristics. TouchIn allows the user to draw on arbitrary regions on the touchscreen without looking at it. This nice sightless feature makes TouchIn very easy to use and also robust to shoulder-surfing and smudge attacks. Comprehensive experiments on Android devices confirm the high security and usability of TouchIn.
71Â citations
Cites background from "Fingerprint Recognition with Embedd..."
...Multi-factor mobile authentication refers to the reliance on more than one authentication paradigm....
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Proceedings Article•
27 Sep 2012TL;DR: The proposed authentication method is analyzed for feasibility and implemented in a prototype as application for the Android operating system, and a biometric database containing photos of the two test devices from 41 test subjects is created.
Abstract: This paper is concerned with the authentication of people on smartphones using fingerphoto recognition. In this work, fingerphotos are captured with the built-in camera of the smartphone. The proposed authentication method is analyzed for feasibility and implemented in a prototype as application for the Android operating system. Algorithms for the capture process are developed to ensure a minimum of quality of the captured photos to enable a reliable fingerphoto recognition. Several methods for preprocessing of the captured samples are analyzed and performant solutions to evaluate the photos are developed to enhance the recognition rates. This is achieved by evaluating a wide range of different parameters and configurations of the algorithms as well as various combinations of preprocessing chains for the captured samples. The operations for preprocessing are selected with respect to their computational effort to guarantee that they can be executed on a smartphone with limited computation and memory capacity. The developed prototype is evaluated in user tests with two different smartphones. Additionally, a biometric database containing photos of the two test devices from 41 test subjects is created. These fingerphotos are used to evaluate and optimize the procedures.
67Â citations
01 Feb 2016
TL;DR: The proposed fully touchless fingerprint recognition system adopts an innovative and less-constrained acquisition setup, does not require contact with any surface or a finger placement guide, and simultaneously captures multiple images while the finger is moving, and proposes novel algorithms for computing 3-D models of the shape of a finger.
Abstract: Touchless fingerprint recognition systems do not require contact of the finger with any acquisition surface and thus provide an increased level of hygiene, usability, and user acceptability of fingerprint-based biometric technologies. The most accurate touchless approaches compute 3-D models of the fingertip. However, a relevant drawback of these systems is that they usually require constrained and highly cooperative acquisition methods. We present a novel, fully touchless fingerprint recognition system based on the computation of 3-D models. It adopts an innovative and less-constrained acquisition setup compared with other previously reported 3-D systems, does not require contact with any surface or a finger placement guide, and simultaneously captures multiple images while the finger is moving. To compensate for possible differences in finger placement, we propose novel algorithms for computing 3-D models of the shape of a finger. Moreover, we present a new matching strategy based on the computation of multiple touch-compatible images. We evaluated different aspects of the biometric system: acceptability, usability, recognition performance, robustness to environmental conditions and finger misplacements, and compatibility and interoperability with touch-based technologies. The proposed system proved to be more acceptable and usable than touch-based techniques. Moreover, the system displayed satisfactory accuracy, achieving an equal error rate of 0.06% on a dataset of 2368 samples acquired in a single session and 0.22% on a dataset of 2368 samples acquired over the course of one year. The system was also robust to environmental conditions and to a wide range of finger rotations. The compatibility and interoperability with touch-based technologies was greater or comparable to those reported in public tests using commercial touchless devices.
67Â citations
29 Dec 2014
TL;DR: TouchIn as mentioned in this paper is a two-factor authentication system for multi-touch mobile devices that allows users to draw on arbitrary regions on the touchscreen without looking at it, which makes it very easy to use and also robust to shoulder-surfing and smudge attacks.
Abstract: Mobile authentication is indispensable for preventing unauthorized access to multi-touch mobile devices. Existing mobile authentication techniques are often cumbersome to use and also vulnerable to shoulder-surfing and smudge attacks. This paper focuses on designing, implementing, and evaluating TouchIn, a two-factor authentication system on multi-touch mobile devices. TouchIn works by letting a user draw on the touchscreen with one or multiple fingers to unlock his mobile device, and the user is authenticated based on the geometric properties of his drawn curves as well as his behavioral and physiological characteristics. TouchIn allows the user to draw on arbitrary regions on the touchscreen without looking at it. This nice sightless feature makes TouchIn very easy to use and also robust to shoulder-surfing and smudge attacks. Comprehensive experiments on Android devices confirm the high security and usability of TouchIn.
61Â citations
References
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TL;DR: This work presents a high-level categorization of the various vulnerabilities of a biometric system and discusses countermeasures that have been proposed to address these vulnerabilities.
Abstract: 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.
1,119Â citations
Book•
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06 Nov 2003
TL;DR: This complete, technical guide details the principles, methods, technologies, and core ideas used in biometric authentication systems and defines and explains how to measure the performance of both verification and identification systems.
Abstract: This complete, technical guide details the principles, methods, technologies, and core ideas used in biometric authentication systems. It explains the definition and measurement of performance and examines the factors involved in choosing between different biometrics. It also delves into practical applications and covers a number of topics critical for successful system integration. These include recognition accuracy, total cost of ownership, acquisition and processing speed, intrinsic and system security, privacy and legal requirements, and user acceptance. The "Guide to Biometrics:" * Debunks myths and candidly confronts problems associated with biometrics research * Details relevant issues in choosing between biometrics, as well as defining and measuring performance * Defines and explains how to measure the performance of both verification and identification systems * Addresses challenges in managing tradeoffs between security and convenience Security and financial administrators, computer science professionals, and biometric systems developers will all benefit from an enhanced understanding of this important technology.
658Â citations
"Fingerprint Recognition with Embedd..." refers methods in this paper
...Such technologies are referred to as live-scan and based on four techniques [9]:...
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TL;DR: In this paper, the authors address the problem of fingerprint individuality by quantifying the amount of information available in minutiae features to establish a correspondence between two fingerprint images, and derive an expression which estimates the probability of a false correspondence between minutia-based representations from two arbitrary fingerprints belonging to different fingers.
Abstract: Fingerprint identification is based on two basic premises: (1) persistence and (2) individuality. We address the problem of fingerprint individuality by quantifying the amount of information available in minutiae features to establish a correspondence between two fingerprint images. We derive an expression which estimates the probability of a false correspondence between minutiae-based representations from two arbitrary fingerprints belonging to different fingers. Our results show that (1) contrary to the popular belief, fingerprint matching is not infallible and leads to some false associations, (2) while there is an overwhelming amount of discriminatory information present in the fingerprints, the strength of the evidence degrades drastically with noise in the sensed fingerprint images, (3) the performance of the state-of-the-art automatic fingerprint matchers is not even close to the theoretical limit, and (4) because automatic fingerprint verification systems based on minutia use only a part of the discriminatory information present in the fingerprints, it may be desirable to explore additional complementary representations of fingerprints for automatic matching.
571Â citations
375Â citations
"Fingerprint Recognition with Embedd..." refers background in this paper
...Biometric template protection [17,18] is one of the most promising solutions to provide a positive-sum of both performance and privacy for biometric systems’ users....
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TL;DR: In this issue, a secure end-to-end touch-less fingerprint verification system is presented and Multiple Random Projections-Support Vector Machine (MRP-SVM) is proposed to secure fingerprint template while improving system performance.
48Â citations
"Fingerprint Recognition with Embedd..." refers background in this paper
...An important question is which of the fingerprint authentication algorithms will work well with fingerprint images produced by cell phone cameras? However, recent research [5,6] have shown that by using low-cost webcam devices it is possible to extract fingerprint information when applying different pre-processing and image enhancements approaches....
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