An effective biometric cryptosystem combining fingerprints with error correction codes

	An effective biometric cryptosystem combining fingerprints with error correction codes
	Li, Peng 1; Yang, Xin1 ; Qiao, Hua 2; Cao, Kai 3; Liu, Eryun 3; Tian, Jie 1,3
发表期刊	EXPERT SYSTEMS WITH APPLICATIONS
	2012-06-01
卷号	39 期号:7 页码:6562-6574
文章类型	Article
摘要	With the emergence and popularity of identity verification means by biometrics, the biometric system which can assure security and privacy has received more and more concentration from both the research and industry communities. In the field of secure biometric authentication, one branch is to combine the biometrics and cryptography. Among all the solutions in this branch, fuzzy commitment scheme is a pioneer and effective security primitive. In this paper, we propose a novel binary length-fixed feature generation method of fingerprint. The alignment procedure, which is thought as a difficult task in the encrypted domain, is avoided in the proposed method due to the employment of minutiae triplets. Using the generated binary feature as input and based on fuzzy commitment scheme, we construct the biometric cryptosystems by combining various of error correction codes, including BCH code, a concatenated code of BCH code and Reed-Solomon code, and LDPC code. Experiments conducted on three fingerprint databases, including one in-house and two public domain, demonstrate that the proposed binary feature generation method is effective and promising, and the biometric cryptosystem constructed by the feature outperforms most of the existing biometric cryptosystems in terms of ZeroFAR and security strength. For instance, in the whole FVC2002 DB2, a 4.58% ZeroFAR is achieved by the proposed biometric cryptosystem with the security strength 48 bits. (C) 2011 Elsevier Ltd. All rights reserved.
关键词	Minutia Triplet Binary Length-fixed Feature Biometric Cryptosystem Fuzzy Commitment Scheme Ecc Security
WOS标题词	Science & Technology ; Technology
关键词[WOS]	FUZZY VAULT ; TEMPLATES ; SECURE
收录类别	SCI
语种	英语
WOS研究方向	Computer Science ; Engineering ; Operations Research & Management Science
WOS类目	Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic ; Operations Research & Management Science
WOS记录号	WOS:000301025300030
引用统计	被引频次：58[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/4055
专题	中国科学院分子影像重点实验室
通讯作者	Tian, Jie
作者单位	1.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China 2.Peking Univ, Satellite & Wireless Commun Lab, Beijing 100871, Peoples R China 3.Xidian Univ, Sch Life Sci & Technol, Xian 710071, Shaanxi, Peoples R China
第一作者单位	中国科学院自动化研究所
通讯作者单位	中国科学院自动化研究所
推荐引用方式 GB/T 7714	Li, Peng,Yang, Xin,Qiao, Hua,et al. An effective biometric cryptosystem combining fingerprints with error correction codes[J]. EXPERT SYSTEMS WITH APPLICATIONS,2012,39(7):6562-6574.
APA	Li, Peng,Yang, Xin,Qiao, Hua,Cao, Kai,Liu, Eryun,&Tian, Jie.(2012).An effective biometric cryptosystem combining fingerprints with error correction codes.EXPERT SYSTEMS WITH APPLICATIONS,39(7),6562-6574.
MLA	Li, Peng,et al."An effective biometric cryptosystem combining fingerprints with error correction codes".EXPERT SYSTEMS WITH APPLICATIONS 39.7(2012):6562-6574.

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