Efficient and Secure Fingerprint Verification for Embedded Devices
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Efficient and Secure Fingerprint Verification for Embedded Devices Shenglin Yang,1 Kazuo Sakiyama,2 and Ingrid Verbauwhede2 1 Department
of Electrical Engineering, University of California, Los Angeles, CA 90095, USA Katholieke Universiteit Leuven, Kasteelpark Arenberg 10, 3001 Leuven-Heverlee, Belgium
2 ESAT-COSIC,
Received 9 March 2005; Revised 22 September 2005; Accepted 21 January 2006 Recommended for Publication by Roger Woods This paper describes a secure and memory-efficient embedded fingerprint verification system. It shows how a fingerprint verification module originally developed to run on a workstation can be transformed and optimized in a systematic way to run real-time on an embedded device with limited memory and computation power. A complete fingerprint recognition module is a complex application that requires in the order of 1000 M unoptimized floating-point instruction cycles. The goal is to run both the minutiae extraction and the matching engines on a small embedded processor, in our case a 50 MHz LEON-2 softcore. It does require optimization and acceleration techniques at each design step. In order to speed up the fingerprint signal processing phase, we propose acceleration techniques at the algorithm level, at the software level to reduce the execution cycle number, and at the hardware level to distribute the system work load. Thirdly, a memory trace map-based memory reduction strategy is used for lowering the system memory requirement. Lastly, at the hardware level, it requires the development of specialized coprocessors. As results of these optimizations, we achieve a 65% reduction on the execution time and a 67% reduction on the memory storage requirement for the minutiae extraction process, compared against the reference implementation. The complete operation, that is, fingerprint capture, feature extraction, and matching, can be done in real-time of less than 4 seconds. Copyright © 2006 Shenglin Yang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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INTRODUCTION
Biometric verification systems offer great security and convenience due to the uniqueness and efficiency of the personal biometric information. However, one of the most significant disadvantages of these systems is that the biometric information cannot be easily recalled. For example, in a fingerprint authentication application, once the finger used as a password is compromised, it never can be used again. In a traditional biometric recognition system, the biometric template is usually stored on a central server during enrollment. The candidate biometric signal captured by the front-end input device is sent to the server where the processing and matching steps are performed. In this case, the safety of the precious biometric information cannot be guaranteed because attacks might occur during the transmission or on the server. Some embedded fingerprint verificat
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