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作 者:朱华虹[1] 贺前华[1] 李艳雄[1] 潘伟锵[1]
机构地区:[1]华南理工大学电子与信息学院,广州510640
出 处:《计算机工程与应用》2014年第13期15-20,共6页Computer Engineering and Applications
基 金:国家自然科学基金(No.60972132;No.61101160);广东省自然科学基金团队项目(No.9351064101000003);广东省自然科学基金博士启动项目(No.10451064101004651)
摘 要: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。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. Voice-print 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 authenti-cation system as the same as in the original feature domain.
分 类 号:TP309[自动化与计算机技术—计算机系统结构]
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