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基于内容的多模态可逆密写方法
引用本文:齐妙,代江艳,王建中,于晓熹,张明.基于内容的多模态可逆密写方法[J].计算机科学,2012,39(11):70-74.
作者姓名:齐妙  代江艳  王建中  于晓熹  张明
作者单位:(东北师范大学计算机科学与信息技术学院 长春 130117) (智能信息处理吉林省高校重点实验室 长春 130117)
摘    要:为了提高生物认证信息在网络传输过程中的安全性,提出一种基于内容相关性分析的多模态双重可逆密写 方法。与现存大多数方法不同,为了充分利用载体图像丰富的内容和提高方法的隐藏性能,首先采用最小二乘回归方 法分析掌纹图像与人脸图像之间的内容相关性,即用人脸图像表示掌纹图像,未被表示的部分掌纹图像被嵌入到相应 的人脸图像中,另外,重构系数作为密钥存储;然后,为了不引起攻击者的注意,将得到的含密人脸图像嵌入到随机选 取的自然载体图像中;最后,将得到含有掌纹信息和人脸信息的含密图像进行传输。提出的方法实现了生物认证信息 的双重可逆信息隐藏,而且哈希函数和密钥的使用提高了该方法的安全性。大量实验结果表明该,方法具有很好的安 全性、不可见性和很高的嵌入容量。特别地,采用双重隐藏机制进一步增强了生物认证信息的安全性,确保了多模态 生物认证的有效性。

关 键 词:密写,内容相关,双重可逆信息隐藏,多模态生物认证

Content-based Reversible Steganographic Method for Multimodal Biometrics
Abstract:A novel dual reversible steganographic method based on content correlation analysis is proposed for enhan- cing the security of biometric information transmitted in the network. Different from the existing approaches, in order to make good use of abundant content of the cover image and improve the performance of data hiding,least square (LS) re- gression method was adopted to exploit the content correlation between the palm image and the face image firstly. In other words, the face image was used to represent the palm image, and the unrepresented part of the palm image was embedded into the corresponding face image. Besides, the reconstruction coefficients were taken as the secret key for se- curity. hhen, the stego-face image was hidden into a nature cover image by the same method for causing much less at- tendon of attackers randomly. Finally, the stego-cov}r image containing palm information and face information were transmitted. The presented method realizes dual reversible data hiding for biometrics and its security is also employed with a hash function and a secret key. The proposed method exhibits good security, invisibility and high capacity. Spe- cially, dual reversible data hiding further improves the security of transmitted biometric information and ensures the va- lidity for multimodal biometric identification.
Keywords:Steganographic  Content correlation  Dual reversible data hiding  Multimodal biometric identification
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