针对生物特征模板的存储及传输安全问题，结合矢量量化声纹识别算法，提出了基于随机变换和动态映射的可撤销模板设计方法．在注册阶段，采用 LBG( Linde- Buzo-Gray) 算法对经过随机变换的声纹特征进行训练，获得码本，码本中的码字被动态映射至不同的随机空间; 在认证阶段，先对认证特征进行与注册阶段相同的随机变换，将其映射至码字所在的随机空间后再进行识别．理论分析表明，随机变换可增强模板的可撤销性，动态映射可增强变换的不确定性．仿真实验结果表明: 随机变换前后系统的身份认证性能保持不变; 当码字和认证特征采用不同随机矩阵进行映射时，系统的等错误率较低，从而验证了该设计方法的可撤销性．

Aiming at the problems of the storage and transmission security of biometric templates,a cancelable tem-plate design method based on both random transformation and dynamic projection is proposed by taking into account the vector quantization (VQ)- based speaker recognition algorithm.In the enrollment stage,the LBG (Linde- Buzo-Gray) algorithm is adopted to train the voiceprint characteristics after random transformation,thus obtaining the codebook.Moreover,the codewords in the codebook are dynamically mapped to different random spaces.In the authentication stage,the voiceprint is mapped to the random space of the codewords by means of the same random transformation as that in the enrollment stage,and the verification is then carried out.Theoretical analyses indicate that the random transformation can improve the cancelability of the voiceprint template,and the dynamic projectioncan increase the uncertainty of the transformation.Simulated results show that the authentication performance of the system remains unchanged before and after the transformation,and that the system EER (Equal Error Ratio) is low when different random matrixes are used to respectively map the codewords and the voiceprint.The cancelability of the proposed method is thus verified.