[1]王科俊,曹逸,姜博威,等.基于纠错码的指静脉加密算法[J].智能系统学报,2017,12(1):55-59.[doi:10.11992/tis.201609028]
WANG Kejun,CAO Yi,JIANG Bowei,et al.Finger vain encryption algorithm based on anerror-correcting code[J].CAAI Transactions on Intelligent Systems,2017,12(1):55-59.[doi:10.11992/tis.201609028]
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WANG Kejun,CAO Yi,JIANG Bowei,et al.Finger vain encryption algorithm based on anerror-correcting code[J].CAAI Transactions on Intelligent Systems,2017,12(1):55-59.[doi:10.11992/tis.201609028]
基于纠错码的指静脉加密算法
《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
12
期数:
2017年第1期
页码:
55-59
栏目:
学术论文—机器感知与模式识别
出版日期:
2017-02-25
- Title:
- Finger vain encryption algorithm based on anerror-correcting code
- Keywords:
- finger vain encryption; error correcting code; finger vain minutiae; biometric encryption; random key; fuzzy vault algorithm
- 分类号:
- TP391.41
- 摘要:
- 对指静脉加密算法进行整体介绍，并加入纠错机制，设计了带纠错功能的指静脉加密算法。利用二进制序列发生器随机生成一个多项式系数形式的密钥，将指静脉特征点加密，在密钥恢复阶段用拉格朗日插值来恢复多项式，并利用循环冗余校验码进行校验，该方法可以找到最精确的密钥来保证多项式的准确度。实验结果表明：利用带有纠错码的模糊金库算法很好地实现了指静脉模板的加密和解密，从而达到了保护生物信息安全的要求；通过密钥长度增长可以提高系统的安全性能。
- Abstract:
- This study presents an overall introduction of a finger vain encryption algorithm. A finger vain encryption algorithm with error correction is then designed by adding an error correction mechanism. This new finger vain encryption algorithm can produce a stochastic key in the form of a multinomial coefficient using a binary system sequencer, an encrypt finger vain, and the Lagrange interpolation value to restore the multinomial during authentication. The accuracy of this algorithm can be ensured using the cyclic redundancy check the code to determine the most accurate key. The experimental results indicate that the fuzzy vault algorithm with error correction can realize well the encryption and decryption of a vein template and meet the requirements of biological information security protection. In addition, the algorithm also indicates that the syste’s safety performance can be enhanced by changing the keys’ length.
- 参考文献/References:
-
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备注/Memo
收稿日期:2016-9-29;改回日期:。
基金项目:国家自然科学基金面上项目（61573114）；黑龙江省自然科学基金面上项目（F2015033）；中央高校基本科研基金项目（HEUCF160415）
作者简介:王科俊,男,1962年生,教授,博士生导师,学科带头人,主要研究方向为模糊混沌神经网络、自适应逆控制理论、可拓控制、网络智能控制、模式识别、多模态生物特征识别、联脱机指纹考试身份鉴别系统、微小型机器人系统。发表学术论文200余篇,出版学术专著3部,主审教材2部;曹逸,女,1993年生,硕士研究生,主要研究方向为模式识别和生物特征识别;邢向磊,男,1983年生,讲师,博士,主要研究方向为多集合度量学习和远离身份识别工作。
通讯作者:邢向磊.E-mail:xingxl@hrbeu.edu.cn.
更新日期/Last Update:
1900-01-01