东北大学学报(自然科学版) ›› 2009, Vol. 30 ›› Issue (6): 817-820.DOI: -

• 论著 • 上一篇    下一篇

基于神经网络和人脸特征的密钥管理方法

张祥德;唐青松;陆小军;朱和贵;   

  1. 东北大学理学院;
  • 收稿日期:2013-06-22 修回日期:2013-06-22 出版日期:2009-06-15 发布日期:2013-06-22
  • 通讯作者: Tang, Q.-S.
  • 作者简介:-
  • 基金资助:
    辽宁省科学技术基金资助项目(002010)

Cipher key management based on neural networks and facial biometrics feature

Zhang, Xiang-De (1); Tang, Qing-Song (1); Lu, Xiao-Jun (1); Zhu, He-Gui (1)   

  1. (1) School of Sciences, Northeastern University, Shenyang 110004, China
  • Received:2013-06-22 Revised:2013-06-22 Online:2009-06-15 Published:2013-06-22
  • Contact: Tang, Q.-S.
  • About author:-
  • Supported by:
    -

摘要: 利用神经网络的联想和记忆功能,将密钥嵌入用户的人脸特征中,给出了一种方便、安全的密钥管理方案.存贮密钥时,提取用户的人脸特征,将其离散化为二进制人脸特征序列,再把用户密钥和其人脸特征序列异或,利用异或得到的结果和一些随机序列训练广义回归神经网络.用户只需要保存训练好的神经网络参数,以及密钥与人脸特征序列异或所得到的结果,无需保存或记忆密钥.当需要获取密钥时,用户只要输入自己的人脸图像,即可由存贮的信息恢复出密钥;而攻击者即使获得了存贮的信息也不能从中得到密钥或用户的人脸特征信息.实验表明,本文给出的密钥管理方法是可行的.

关键词: 神经网络, 人脸识别, 密钥管理, 主成分分析

Abstract: A convenient and secure management scheme of cipher key is proposed taking advantage of the associative memory function from neural networks and embedding the cipher key in the user's facial biometrics feature. Extracting the user's facial biometrics feature and discretizing it to be a binary sequence through the principal component analysis (PCA), and the key is integrated into the facial biometrics sequence via XOR (exclusive-OR), and the XOR result and some random sequences are used to train the generalized regression neural networks. Eventually, what a user has to do is just storing the trained parameters of neural networks, XOR result of the key and facial biometrics sequence without the key to be stored or memorized. Then, only if a user inputs his own face image the key can be restored from the stored data whenever the key is required. An attacker is impossible to get the key or the information on user's facial biometrics feature, even if he has obtained the stored data. The experiment results showed that the proposed scheme is feasible.

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