Fingerprint Template Protection Algorithm Based on Bit String XOR and Scrambling Transformation
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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.Abstract: Aiming at the problems of low accuracy and poor security performance of the existing fingerprint template protection algorithm, A fingerprint template protection algorithm based on bit string XOR and scrambling transformation is proposed. Based on the existing two-dimensional mapping algorithm, the algorithm performs XOR and random index scrambling transformation on the obtained bit string, the algorithm effectively combines linear and nonlinear transformations, thereby expanding the key space and enhancing the security of the fingerprint template. Theoretical analysis and simulation results show that for the key leakage scenario, the equal error rate (EER) of the algorithm in the database FVC2002 DB1, DB2 is 0.08 % and 0.75 %, respectively, compared with existing methods, it has better accuracy and security.
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Key words:
- Fingerprint template /
- security /
- bit string /
- XOR /
- scrambling
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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
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 DB1 DB2 DB3 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 高 中 低 
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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 $[2,4]$
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表 3 密钥泄露时不同参数的EER (%)
Table 3 EER of different parameters (%)
$r_{\rm{\min}}$ $r_{\rm{\max}}$ $G_{x}$ $G_{y}$ $\rho_{1}$ $\rho_{2}$ $w$ DB1 DB2 $16$ 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 $17$ $15$ $3.732$ $-0.09$ $4$ $0.98$ $2.64$
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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 DB1 DB2 DB3 DB1 DB2 DB3 SCFT 算法 − − − 5.12 − 16.99 本文算法 0 0 0 0.08 0.75 3.26
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表 6 依次增加不同改进算法的EER (%)
Table 6 EER of add different improved algorithms (%)
算法 DB1 DB2 密钥安全 密钥泄露 密钥安全 密钥泄露 改进前算法 0 3.26 0 2.915 随机异或 0 1.05 0 1.58 行间异或 0 0.44 0 1.24 随机索引置乱 0 0.08 0 0.75
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