计算机应用 ›› 2012, Vol. 32 ›› Issue (06): 1623-1626.DOI: 10.3724/SP.J.1087.2012.01623

• 信息安全 • 上一篇    下一篇

基于人像图像的随机序列发生器

谭阳1,2,唐德权1,3,唐钊轶1,2   

  1. 1. 湖南师范大学 数学与计算机科学学院,长沙 410081
    2. 湖南网络工程职业学院 信息工程系,长沙 410004
    3. 湖南警察学院 计算机科学技术系,长沙 410138
  • 收稿日期:2011-11-24 修回日期:2012-02-02 发布日期:2012-06-04 出版日期:2012-06-01
  • 通讯作者: 谭阳
  • 作者简介:谭阳(1979-),男,湖南望城人,讲师,主要研究方向:信息安全、智能计算;〓唐德全(1979-),男,湖南永州人,讲师,主要研究方向:数据挖掘、网络安全;〓唐钊轶(1981-),男,湖南益阳人,讲师,主要研究方向:数值计算、信息编码。
  • 基金资助:
    国家自然科学基金资助项目

Portrait image based on random sequence generator

TAN Yang1,2,TANG De-quan1,3,TANG Zhao-yi1,2   

  1. 1. College of Mathematics and Computer Science, Hunan Normal University, Changsha Hunan 410081,China
    2. Department of Information Engineering, Network Engineering Vocational College, Changsha Hunan 410004,China
    3. Department of Computer Science and Technology, Hunan Police Academy, Changsha Hunan 410138,China
  • Received:2011-11-24 Revised:2012-02-02 Online:2012-06-04 Published:2012-06-01
  • Contact: TAN Yang

摘要: 通过利用人像面部表情特征的差异性和获取(拍摄)过程中随机性,提出了一种新的随机序列生成方法;通过将图像获取过程中的随机噪声与人体生物特征相结合的方式产生随机源。仿真测试表明,该方法产生的随机序列不具有线性相关性和非线性相关性,具有优良的均匀度和FIPS PUB 140-2及NIST 800-22测试通过率,能够满足信息安全的需要,并且方法简单,易于实现。

关键词: 随机序列, 人像图像, 面部特征, 相关性分析, 统计性分析

Abstract: Random sequence as the basis for information security, the quality depends on its use of random source, how to get high-quality random source research in the field of information security is one of the difficulties. Portrait facial features through the use of the difference and get (shoot) random process, a new image as a random source of portraits of random sequence generation methods; through the image acquisition process and the human biological characteristics of random noise a combination of random source. Simulation tests show that this method does not have a random sequence generated by linear correlation and nonlinear correlation, with excellent uniformity and FIPS PUB 140-2 and NIST 800-22 test pass rates to meet the needs of information security, and the method is simple and easy to implement.

Key words: Random sequence, portrait image, facial features, correlation analysis, statistical analysis