基于比特流的虹膜特征数据的隐藏算法

对生物特征数据的攻击是生物特征识别自身安全的主要威胁。为了提高虹膜特征数据的安全性，根据现有主要的虹膜识别方法中特征模板的数据特性和基于汉明距的比对方法，提出一种基于比特流的将虹膜特征模板数据嵌入人脸图像的数据隐藏算法。实验结果表明，该算法具有较强的隐蔽性，隐藏算法本身误码率为零，计算效率高，不会影响虹膜识别技术本身的性能，能够有效保护特征模板数据，增强虹膜识别系统自身的安全性。

Bit-stream Based Iris Features Data Hidden Method

Attacks pointing to biometric data are the basic menace of biometrics self-security. For improving the security of iris features data, this paper proposes a bit stream based data hidden approach by embedding iris features data into a face image which is applicable to the dominant method of present iris recognition technologies. While having the high computation efficiency and the zero-decoding-errorrate, the method embedding a key biometric feature into another biometric feature for transmission in a biometrics security net can deceive attackers better, and also is not repressive to the excellent performance of the iris recognition. Experiments show that the data hidden approach can effectively protect iris features data and enhance the iris recognition system self-security.