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随着生物特征识别技术应用的愈加深入,生物特征所涉及到的人的隐私以及由此带来的安全性问题逐渐暴露出来.生物特征加密结合了生物识别技术和加密技术,将生物特征和密钥融合,使得密钥和生物特征本身都很难从系统存储的模板中获取,当且仅当活体生物特征提交给系统时密钥才会重新生成.生物特征加密的天然模糊性必然要求相应的加密技术具备容错性,基于模糊身份的公钥加密可自然用于生物特征加密.为弥补直接使用模糊身份加密造成的开销大的不足,也为了更精确的进行指纹识别,本文从模糊身份加密出发,构造了一个标准模型下新的自适应安全的模糊身份加密算法,并在此基础上借助密钥共享算法构造了双阈值的指纹生物特征加密方案.与已有的指纹加密方案相比,本文提出的方案不仅在开销上优于直接使用模糊身份加密的指纹加密,还能分别从全局与局部两方面完成指纹的识别与加密,使得方案更具实用性.同时经过数学证明,本文提出的加密方案在标准模型下是自适应安全的.
As the application of biometrics becomes more and more in-depth, the privacy of the people involved in the biometrics and the consequent security problems are gradually exposed.Biological Features Encryption combines the biometrics and the encryption technology, Key fusion makes it very difficult for the key and the biological feature to be obtained from the system stored template, and the key will only be regenerated if and only if the biological feature is submitted to the system. The natural ambiguity of biometric encryption necessarily requires that the corresponding Encryption technology is fault-tolerant, and public-key encryption based on ambiguous identity can naturally be used for biometric encryption.In order to make up for the large overhead caused by the direct use of ambiguous identity encryption and also for more accurate fingerprinting, , A new adaptive security fuzzy identity encryption algorithm is constructed based on the standard model, and on this basis, a bi-threshold fingerprint biometric encryption scheme is constructed by using the key sharing algorithm.Compared with the existing fingerprint encryption scheme, The proposed scheme not only outperforms the fingerprint encryption using fuzzy identity encryption directly, but also from the whole Both partial and complete fingerprint identification and encryption scheme that is more practical while mathematically proven, encryption scheme proposed in the standard model is adaptive safe.