计算机应用 ›› 2011, Vol. 31 ›› Issue (06): 1528-1530.DOI: 10.3724/SP.J.1087.2011.01528

• 信息安全 • 上一篇    下一篇

基于细胞神经网络超混沌特性的图像加密新算法

任晓霞,廖晓峰,熊永红   

  1. 重庆大学 计算机学院,重庆400044
  • 收稿日期:2010-11-09 修回日期:2011-01-16 发布日期:2011-06-20 出版日期:2011-06-01
  • 通讯作者: 任晓霞
  • 作者简介:任晓霞(1986-),女,山东德州人,硕士研究生,主要研究方向:CNN图像处理、稳定性理论;廖晓峰(1964-),男,重庆人,教授,博士,主要研究方向:信息安全、非线性控制理论;熊永红(1986-),女,河南开封人,硕士研究生,主要研究方向:CA、混沌加密、信息安全。
  • 基金资助:
    国家自然科学基金资助项目;重庆市自然科学基金重点资助项目

New image encryption algorithm based on cellular neural network

REN Xiaoxia,LIAO Xiaofeng,XIONG Yonghong   

  1. College of Computer Science, Chongqing University, Chongqing 400044, China
  • Received:2010-11-09 Revised:2011-01-16 Online:2011-06-20 Published:2011-06-01
  • Contact: REN Xiaoxia

摘要: 针对一般流密码对明文变化不敏感的缺陷,基于细胞神经网络(CNN),提出一种图像加密新算法。以一个6维CNN产生的超混沌系统作为密钥源,并根据明文图像各点像素值的逻辑运算结果选取密钥;同时使用像素位置置乱和像素值替代两种方法对数字图像进行加密。实验表明,该算法加密效果好,NPCR值和密钥敏感性高(>0.996),满足数字图像加密安全性的要求,同时具有计算简单、易于实现、能提高数字图像传输的安全性等特点。

关键词: 细胞神经网络, 超混沌, 混沌序列, 图像加密

Abstract: In this paper, a new image encryption algorithm was presented by employing Cellular Neural Network (CNN). The main objective was to solve the problem of traditional stream ciphers insensitivity to the change of plain text. By using a hyper chaotic system of 6-D CNN as the key source, selecting the secret key based on the results of logical operations of pixel values in the plain image, and introducing simultaneously both position permutation and value transformation, the new algorithm was presented. It is shown that both NPCR value and the sensitivity to key (>0.996) can meet the security requirements of image encryption. The simulation process also indicates that the algorithm is relatively easy to realize with low computation complexity, and ensures, accordingly, the secure transmission of digital images.

Key words: Cellular Neural Network (CNN), hyperchaos, chaotic sequence, image encryption