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Title: An iris cryptosystem for information security
Authors: Wu, Xiangqian
Qi, Ning
Wang, Kuanquan
Zhang, David D.
Subjects: Biometrics
Cryptography
Data storage equipment
Internet
Network protocols
Sensor networks
Signal processing
Issue Date: 2008
Publisher: IEEE Computer Society
Citation: IIH-MSP 2008 : 2008 fourth International Conference on Intelligent Information Hiding and Multimedia Signal Processing : 15-17 August 2008, Harbin, China : proceedings, p. 1533-1536.
Abstract: Securing information is a key issue in the field of network security and cryptography is one of the most effective ways to enhance information security. Biometric cryptography is a technique using biometric features to encrypt the data, which can improve the security of the encrypted data and overcome the shortcomings of the traditional cryptography. This paper proposes a novel biometric cryptosystem based on the most accurate biometric feature - iris. In this system, a 256-dimension textural feature vector is extracted from the preprocessed iris image by using a set of 2-D Gabor filters. And then a modified fuzzy vault algorithm is employed to encrypt and decrypt the data. Experimental results demonstrate the feasibility of the proposed system.
Rights: © 2008 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.
Type: Conference Paper
URI: http://hdl.handle.net/10397/1212
ISBN: 9780769532783
Appears in Collections:COMP Conference Papers & Presentations

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