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基于比特串异或和置乱变换的指纹模板保护算法

党力 张雪锋 惠妍

党力, 张雪锋, 惠妍. 基于比特串异或和置乱变换的指纹模板保护算法. 自动化学报, 2020, 46(12): 2681−2689 doi: 10.16383/j.aas.c190011
引用本文: 党力, 张雪锋, 惠妍. 基于比特串异或和置乱变换的指纹模板保护算法. 自动化学报, 2020, 46(12): 2681−2689 doi: 10.16383/j.aas.c190011
Dang Li, Zhang Xue-Feng, Hui Yan. Fingerprint template protection algorithm based on bit string XOR and scrambling transformation. Acta Automatica Sinica, 2020, 46(12): 2681−2689 doi: 10.16383/j.aas.c190011
Citation: Dang Li, Zhang Xue-Feng, Hui Yan. Fingerprint template protection algorithm based on bit string XOR and scrambling transformation. Acta Automatica Sinica, 2020, 46(12): 2681−2689 doi: 10.16383/j.aas.c190011

基于比特串异或和置乱变换的指纹模板保护算法

doi: 10.16383/j.aas.c190011
基金项目: 国家自然科学基金(61301091), 陕西省自然科学基础研究计划青年项目(2017JQ6010)资助
详细信息
    作者简介:

    党力:西安邮电大学网络空间安全学院硕士研究生. 主要研究方向为生物特征识别. 本文通信作者. E-mail: dangli_xupt@163.com

    张雪锋:博士, 西安邮电大学网络空间安全学院教授. 主要研究方向为信息安全. E-mail: zhangxuefeng3@163.com

    惠妍:西安邮电大学通信与信息工程学院硕士研究生. 主要研究方向为生物特征识别. E-mail: huiyan_mini@163.com

Fingerprint Template Protection Algorithm Based on Bit String XOR and Scrambling Transformation

Funds: Supported by National Natural Science Foundation of China (61301091) and Natural Science Basic Research Plan in Shaanxi Province of China (2017JQ6010)
  • 摘要: 针对现有指纹模板保护算法存在的准确性较低、安全性能较差的问题, 提出一种基于比特串异或和置乱变换的指纹模板保护算法. 该算法在已有二维映射算法的基础上, 对得到的比特串进行异或和随机索引置乱变换, 有效地将线性和非线性变换相结合, 扩展了密钥空间, 增强了指纹模板的安全性. 理论分析和仿真结果表明, 对于密钥泄露场景, 该算法在数据库FVC2002 DB1和DB2中的等错误率(Equal error rate, EER)分别为0.08 %和0.75 %, 与现有算法相比, 具有较好的准确性和安全性.
  • 图  1  细节点分布示意图

    Fig.  1  Minutiae point distribution diagram

    图  2  算法的基本流程

    Fig.  2  Basic flow of the algorithm

    图  3  有效细节点集的选取

    Fig.  3  Selection of effective minutiae point set

    图  4  细节点投影过程

    Fig.  4  Minutiae point projection process

    图  5  异或操作的基本流程

    Fig.  5  Basic flow of XOR operation

    图  6  指纹特征串的行间异或

    Fig.  6  Inter-row XOR process of feature strings

    图  7  比特串的随机索引置乱

    Fig.  7  Random index scrambling of feature strings

    图  8  本文算法与SCFT算法的ROC曲线对比图

    Fig.  8  ROC curves of SCFT and proposed algorithms

    图  9  密钥泄露时改进前的真假匹配分布

    Fig.  9  Genuine and imposter distributions before improvement in the stolen-key scenario

    图  10  密钥泄露时改进后的真假匹配分布

    Fig.  10  Genuine and imposter distributions after improvement in the stolen-key scenario

    图  11  密钥泄露时真假匹配分布

    Fig.  11  Genuine and imposter distributions in the stolen-key scenario

    图  12  伪假匹配分布

    Fig.  12  Pseudo-imposter match distribution

    表  1  数据库FVC2002 DB1、DB2和DB3的参数

    Table  1  Parameters of the FVC2002 DB1, DB2 and DB3

    指纹数据库DB1DB2DB3
    传感器类型光纤光纤电容
    手指数量$100$$100$$100$
    每枚手指样本个数$8$$8$$8$
    分辨率 (dpi)$500$$569$$500$
    图像尺寸$388\times374$$296\times560$$300\times300$
    图像质量
    下载: 导出CSV

    表  2  不同参数的取值范围

    Table  2  Range of different parameters

    参数参数描述参数范围
    $r_{\rm{\min}}$环形区域最小半径$\{ 15,16,17 \}$
    $r_{\rm{\max}}$环形区域最大半径$\{ 100,240 \}$
    $G_{x}$二维网格的长$\{13, 14,15, 16 \}$
    $G_{y}$二维网格的宽$\{ 7,14 \}$
    $\rho_{1,2}$投影直线斜率$[-2,4]$
    $w$步长$[2,4]$
    下载: 导出CSV

    表  3  密钥泄露时不同参数的EER (%)

    Table  3  EER of different parameters (%)

    $r_{\rm{\min}}$$r_{\rm{\max}}$$G_{x}$$G_{y}$$\rho_{1}$$\rho_{2}$$w$DB1DB2
    $16$100$13$$7$$0.577$$-1.73$$2$$0.25$$2.02$
    $16$110$14$$8$$0.839$$-1$$2$$0.17$$1.67$
    $16$120$14$$9$$1$$-0.84$$2$$0.22$$1.82$
    ${\bf 16}$${\bf 140}$${\bf 14}$${\bf 9}$${\bf 1.192}$${\bf -0.58}$${\bf 3}$${\bf 0.08}$${\bf 0.75}$
    $16$160$14$$9$$1.192$$-0.58$$4$$0.12$$1.46$
    $16$180$14$$9$$1.192$$-0.36$$4$$0.15$$1.66$
    $16$200$14$$10$$1.732$$-0.26$$4$$0.42$$2.30$
    $16$220$15$$12$$2.144$$-0.18$$4$$1.12$$3.11$
    $16$240$16$$14$$2.747$$-0.14$$4$$0.68$$1.81$
    $16$260$17$$15$$3.732$$-0.09$$4$$0.98$$2.64$
    下载: 导出CSV

    表  4  SCFT算法和本文算法的EER比较(%)

    Table  4  EER comparison between the SCFT algorithms and proposed algorithms (%)

    算法密钥安全密钥泄露
    DB1DB2DB3DB1DB2DB3
    SCFT 算法5.1216.99
    本文算法0000.080.753.26
    下载: 导出CSV

    表  5  不同算法的EER比较(%)

    Table  5  EER comparison of different algorithms (%)

    算法DB1DB2DB3
    Ahmad 等[22]96$27$
    Yang 等[23]5.934
    Jin 等[24]4.361.77
    Wang 等[25]3.557.5
    Das 等[26]2.273.79
    Ali 等[27]2.13.1
    Prasad 等[21]1.621.332.64
    惠妍等[28]0.17170.0606
    本文算法0.080.753.26
    下载: 导出CSV

    表  6  依次增加不同改进算法的EER (%)

    Table  6  EER of add different improved algorithms (%)

    算法DB1DB2
    密钥安全密钥泄露密钥安全密钥泄露
    改进前算法03.2602.915
    随机异或01.0501.58
    行间异或00.4401.24
    随机索引置乱00.0800.75
    下载: 导出CSV
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出版历程
  • 收稿日期:  2019-01-04
  • 录用日期:  2019-09-02
  • 网络出版日期:  2020-12-29
  • 刊出日期:  2020-12-29

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