基于同态加密的声纹模板设计及其分析

结合声纹特征和VQ（Vector Quantization）识别算法的特点，在对整数同态加密算法进行改进的基础上，提出基于同态加密（homomorphic encryption scheme）的声纹模板保护方法。将实数形式的码本和认证声纹特征转化为整数，采用改进的整数同态加密算法对数据加密并计算密文的欧氏距离分量差，运算结果经解密后用于计算平均最小量化误差最终进行决策输出。该方法克服了实数同态加密算法密文泄漏明文的大小关系、小数和正负数信息等缺陷，并能抵抗已知明文攻击。实验结果表明，加密后系统的身份认证性能可基本保持，验证了方法的有效性。

Homomorphic encryption scheme based voiceprint template design and analysis

A voiceprint template protection method based on homomorphic encryption scheme is proposed, which takes the characteristics of speech features and Vector Quantization（VQ） speaker recognition algorithms into account. Voiceprint features and codewords are transformed into non-negative integers. Components of Euclidean distance are calculated in the ciphertext domain by improved homomorphic encryption algorithm in the range of the integer. Decision is made according to the average minimum quantization error which is calculated with decrypting homomorphically component addition of VQ distance. The ciphers don’t leak the decimal fraction and sign information of plain text and can resist known plaintext attacks. The experimental results demonstrate the proposed method can keep the performance of authentication system as the same as in the original feature domain.