计算机工程与应用 ›› 2018, Vol. 54 ›› Issue (21): 194-200.DOI: 10.3778/j.issn.1002-8331.1707-0177

• 图形图像处理 • 上一篇    下一篇

细胞神经网络与改进AES的超混沌图像加密方案

王  勇,朱  光,王  瑛   

  1. 广东工业大学 计算机学院,广州 510003
  • 出版日期:2018-11-01 发布日期:2018-10-30

Hyperchaotic image encryption algorithm based on cellular neural network and AES algorithm

WANG Yong, ZHU Guang, WANG Ying   

  1. School of Computers, Guangdong University of Technology, Guangzhou 510003, China
  • Online:2018-11-01 Published:2018-10-30

摘要: 针对当前一类基于混沌系统的图像加密算法的应用进行研究,提出了一种五维细胞神经网络和AES(高级加密标准)加密算法相结合的超混沌图像加密算法。该方法定义了五个数和提取一个与明文像素值相关的参数作为密钥,通过细胞神经网络生成的超混沌序列作为AES加密算法的目标密钥;将明文与目标密钥进行异或处理;将目标密钥代入算法进行若干次AES加密算法进行加密得到密文。通过实验仿真表明,该算法能较好地抵抗差分攻击、统计特性分析等,而且还能有效抵抗明文攻击,加密效果较好。

关键词: 五维细胞神经网络, AES加密算法, 超混沌, 图像加密

Abstract: By analyzing the application of image encryption algorithm based on chaotic system in recent years, a hyperchaotic image encryption algorithm combining five-dimensional cellular neural network and AES(Advanced Encryption Standard) encryption algorithm is proposed. This method first defines five numbers and extracts a hyperchaotic sequence generated by the cellular neural network as a key for the parameters associated with the plaintext pixel values as the target key of the AES encryption algorithm. Then, the plaintext is carried out with the target key Exclusive OR processing. Finally, the target key is substituted into the algorithm for several times AES encryption algorithm to encrypt the ciphertext. Simulation results show that the proposed algorithm can resist resistance attack and statistical characteristic analysis, and it can effectively resist plain attack and achieve good encryption effect.

Key words: 5D of cellular neural network, Advanced Encryption Standard(AES), hyperchaotic, image encryption