首页> 外文期刊>Information Forensics and Security, IEEE Transactions on >A Security-Enhanced Alignment-Free Fuzzy Vault-Based Fingerprint Cryptosystem Using Pair-Polar Minutiae Structures
【24h】

A Security-Enhanced Alignment-Free Fuzzy Vault-Based Fingerprint Cryptosystem Using Pair-Polar Minutiae Structures

机译:使用对-极性细节结构的安全性增强,无比对,基于模糊保管库的指纹密码系统

获取原文
获取原文并翻译 | 示例
           

摘要

Alignment-free fingerprint cryptosystems perform matching using relative information between minutiae, e.g., local minutiae structures, is promising, because it can avoid the recognition errors and information leakage caused by template alignment/registration. However, as most local minutiae structures only contain relative information of a few minutiae in a local region, they are less discriminative than the global minutiae pattern. Besides, the similarity measures for trivially/coarsely quantized features in the existing work cannot provide a robust way to deal with nonlinear distortions, a common form of intra-class variation. As a result, the recognition accuracy of current alignment-free fingerprint cryptosystems is unsatisfying. In this paper, we propose an alignment-free fuzzy vault-based fingerprint cryptosystem using highly discriminative pair-polar (P-P) minutiae structures. The fine quantization used in our system can largely retain information about a fingerprint template and enables the direct use of a traditional, well-established minutiae matcher. In terms of template/key protection, the proposed system fuses cancelable biometrics and biocryptography. Transforming the P-P minutiae structures before encoding destroys the correlations between them, and can provide privacy-enhancing features, such as revocability and protection against cross-matching by setting distinct transformation seeds for different applications. The comparison with other minutiae-based fingerprint cryptosystems shows that the proposed system performs favorably on selected publicly available databases and has strong security.
机译:无对齐指纹密码系统使用细节之间的相对信息(例如局部细节结构)执行匹配是有希望的,因为它可以避免识别错误和模板对齐/注册导致的信息泄漏。但是,由于大多数局部细节结构仅包含局部区域中少数细节的相对信息,因此它们比全局细节模式的判别力小。此外,现有工作中对粗略/粗略量化特征的相似性度量无法提供一种可靠的方式来处理非线性失真,这是类内变异的一种常见形式。结果,当前的无对准指纹密码系统的识别精度令人不满意。在本文中,我们提出了一种使用高度判别性对极性(P-P)细节结构的基于无对齐的模糊库的指纹密码系统。我们系统中使用的精细量化可以在很大程度上保留有关指纹模板的信息,并可以直接使用传统的,完善的细节匹配器。在模板/密钥保护方面,建议的系统融合了可取消的生物识别和生物密码技术。在编码之前对P-P细节结构进行转换会破坏它们之间的相关性,并且可以通过为不同的应用设置不同的转换种子来提供增强隐私的功能,例如可撤销性和防止交叉匹配的功能。与其他基于细节的指纹密码系统的比较表明,该系统在选定的公共数据库上具有良好的性能,并且具有很强的安全性。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号