User authentication, which refers to the process of verifying the identity of a user, is becoming an important security requirement in various embedded systems. While conventional solutions for user authentication have relied on password-based mechanisms, they are increasingly being replaced by biometric technologies such as fingerprint, face, and voice recognition, which are known to provide higher levels of security for user authentication. This paper investigates the problem of supporting efficient fingerprint-based user authentication in embedded systems. For improving the performance of fingerprint-based authentication, we propose hardware/software enhancements that include a generic set of custom instruction extensions to an embedded processor's instruction set architecture, a memory-aware software re-design, and fixed-point arithmetic. We believe that the custom instruction set extensions proposed in this work are generic enough to speed up many fingerprint matching algorithms and even other biometric algorithms. Our experiments with an open-source, high-fidelity fingerprint authentication algorithm and a testbed featuring a commercial extensible processor show that performance is improved by a factor of 10.4X when using the proposed enhancements, while incurring modest overheads.

/pdf/efficient-fingerprint-based-user-authentication-for-embedded-189rr9361c.pdf

Efficient fingerprint-based user authentication for embedded systems

We propose a light-weight fingerprint matching algorithm that can be executed inside the devices with a limited computational power. The algorithm is based on the minutiae local structures (the “neighborhoods”), that are invariant with respect to global transformations like translation and rotation. The match algorithm has been implemented inside a smartcard over the Java CardTM platform, meeting the individual’s need for information privacy and overall authentication procedure security. The main characteristic of the algorithm is to have an asymmetric behavior, in respect to the execution time, between correct positive and negative matches. The performances in terms of authentication reliability and speed were tested on some databases from the Fingerprint Verification Competition 2002 and 2004 editions (FVC2002 and FVC2004). Moreover, our procedure showed better reliability when compared with a related algorithm on the same database. We can achieve a false acceptance rate (FAR) of 0.1%, a false rejection rate of about 6%, and from 0.3 to 8 s to match most of the finger pairs during the FAR tests.

/pdf/an-asymmetric-fingerprint-matching-algorithm-for-java-card-21l5foml9v.pdf

An asymmetric fingerprint matching algorithm for Java Card TM

Biometrics-based authentication systems offer enhanced security and user convenience compared to traditional token-based (e.g., ID card) and knowledge-based (e.g., password) systems. However, the increased deployment of biometric systems in several commercial and government applications has raised questions about the security of the biometric system itself. Since the biometric traits of a user cannot be replaced if compromised, it is imperative that these systems are suitably secure in order to protect the privacy of the user as well as the integrity of the overall system. In this paper, we first investigate several methods that have been proposed in the literature to increase the security of the templates residing in a biometric system. We next propose a novel fingerprint matching architecture for resource-constrained devices (e.g., smart cards) that ensures the security of the minutiae templates present in the device. Experimental results describing the impact of several system parameters on the matching performance as well as the computational and storage costs are provided. The proposed architecture is shown to enhance the security of the minutiae templates while maintaining the overall matching performance of the system.

/pdf/secure-fingerprint-matching-with-external-registration-7j9g1rexyd.pdf

Secure fingerprint matching with external registration

v The dissertation of Dalei Wu is approved and is acceptable in quality and form for publication on microfilm: Dedication To my wife and my daughter for their endless love, patience and encouragement. Also to my parents and brother, without their support, I could never have succeeded. Acknowledgements It is an exploratory journey of the mind to write a thesis. Many interesting discoveries on the way to the final draft are made by deviating from the straight path and topic of the thesis. At the same time, you know that there is a path, journey, and goal lying ahead of you-a thought which ensures that you do not go to far astray. In the course of this academic journey, many people have contributed ideas and comments to the present thesis. I would like to thank all of them for making it a wonderful and enriching enterprise. First and foremost I wish to thank the chairman of the committee and one of my supervisors Prof. Barry. He always shares his strongest sense of humour with everyone, also including me, which skilfully changes the hard work into the much easier and happier one. Each time I meet a problem and go to discuss it with him, he always shed great lights on the problem by his profound thoughts and knowledge across multiple disciplines. It will be beneficial to me throughout all my life to learn from him. Many thanks go also to my second supervisor, Prof. Jacques Koreman for his unwavering support, advice and patience. He gave me so much help that I could never forget. When I first arrived at Saarbrücken, It was him to pick up my family and me from the railway station in a very late evening. Later, he arranged everything I needed so well that I was able to be fully involved in my research work immediately. More important, he taught me the techniques and skills in almost every aspect which I need now for my research and later for my academic career. No matter how much gratitude I give him, it would never too much for him. Further thanks go to my third supervisor Dr. Andrew Morris. He always gives me a lot of help on research direction and working attitudes. He has a solid background on mathematics which I can learn so much from him. He is a professional researcher in the domain of speech …

/pdf/discriminative-preprocessing-of-speech-towards-improving-1avfmn00lr.pdf

Discriminative Preprocessing of Speech: Towards Improving Biometric Authentication

In this paper, we present a fast, high accurate, and multiplierless fingerprint authentication method. Firstly, the fingerprint image is captured and performed noise canceling by a binary low-pass filter. Secondly, we estimate the displacement of the fingerprint pattern by means of directional image matching, and then circular profile features of the fingerprint are extracted for verification matching. Finally, the proposed method is implemented in an 8-bits microcontroller run at 25 MHz. The experiment results show that the proposed system possesses excellent recognition performance and efficiency. The advantage of the low complexity architecture is to apply fingerprint recognition in a low cost, resource-constrained embedded environment.

An embedded fingerprint authentication system with reduced hardware resources requirement

Fingerprint sensors are getting small enough to be included in mobile devices to enable fingerprint verification be employed as an authentication tool when using the mobile devices for secure transactions. Fingerprint verification, however, is a computing intensive technology that requires a lot of floating-point computation. Unfortunately, the embedded processors in most mobile devices do not support floating-point hardware. In this paper, we present the implementation of a fingerprint verification process in an embedded system environment based the StrongArm processor and the embedded Linux operating system. The success of the implementation relies on the use of a fixed-point arithmetic only. The fingerprint verification component, the fixed-point component as well as the technique employed to pair up the two components are described in details. In particular, we estimated the required precisions in the fixed-point representations before conducting experiments. Through our results, we further show that not only the fixed-point implementation achieves the goal of significant speed improvement but is almost as reliable as the floating-point counterparts.

Efficient implementation of fingerprint verification for mobile embedded systems using fixed-point arithmetic

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Efficient implementation of fingerprint verification for mobile embedded systems using fixed-point arithmetic