使用部分排序和随机查找表映射的可撤销虹膜模板

IF 0.6 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Mulagala Sandhya, Dilip Kumar Vallabhadas, Shubham Rathod
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引用次数: 1

摘要

在过去的几年里,生物识别系统最终对模板信息的溢出无能为力。如果生物识别模板被盗,它将永久丢失,无法恢复或重新签发。在这里,我们使用虹膜生物识别技术,因为它的准确性很高。在本文中,我们开发了一种新的可取消的生物识别方案,使用索引优先(IFO)哈希加上部分排序技术。IFO散列使用了新的机制,称为p阶Hadamard乘积和模阈值函数,与部分排序技术配对,这大大加强了它的进一步。我们使用了非常复杂的CASIA-v3数据库,它为我们的实验提供了广泛的虹膜模板。与之前的可取消方案相比,这些实验结果的分析为我们提供了良好的准确性和强大的抵抗各种隐私和安全攻击的能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Revocable iris templates using partial sort and randomised look-up table mapping
In the ongoing years, biometric systems end up helpless against the spillage of template information. If a biometric template is stolen, it is lost permanently and cannot be restored or reissued. Here, we use iris biometric because of its high accuracy. In this paper, we develop a new cancellable biometric scheme using the indexing-first-one (IFO) hashing coupled with a technique called partial sort. The IFO hashing uses new mechanisms called the P-order Hadamard product and modulo threshold function paired with the partial sort technique which has considerably strengthened it further. We used the very sophisticated CASIA-v3 database which provides us with a wide range of iris templates for our experiments. As compared to the previous cancellable schemes, the analysis of the results of these experiments provides us with good accuracy and strong resistance to various privacy and security attacks.
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来源期刊
International Journal of Biometrics
International Journal of Biometrics COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-
CiteScore
1.50
自引率
0.00%
发文量
46
期刊介绍: Biometrics and human biometric characteristics form the basis of research in biological measuring techniques for the purpose of people identification and recognition. IJBM addresses the fundamental areas in computer science that deal with biological measurements. It covers both the theoretical and practical aspects of human identification and verification.
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