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基于CNN和CML的时空混沌序列图像加密算法
  • 期刊名称:计算机应用研究, Vol.24, No.8, pp.159-161, 2007.
  • 时间:0
  • 分类:TP309.2[自动化与计算机技术—计算机系统结构;自动化与计算机技术—计算机科学与技术]
  • 作者机构:[1]重庆科技学院电子信息工程学院,重庆400050, [2]电子科技大学计算机科学与工程学院,成都610054, [3]重庆大学计算机科学与工程学院,重庆400044
  • 相关基金:国家自然科学基金资助项目(60573047);重庆市科委自然科学基金资助项目(CSTC,2005BB2050);重庆市教委科学技术研究基金资助项目(KJ051402)
  • 相关项目:基于混沌密码学的安全JPEG2000图像编码系统的设计和实现
中文摘要:

基于细胞神经网络(CNN)和耦合映像格子模型(CML),提出了一种密钥长度为128 bit的对称图像加密算法。该算法用具有复杂动力学行为的CNN网络和分段线性混沌映射去驱动CML模型,以快速产生时空混沌序列,并与原始图像异或完成加密过程。算法分析表明具有密钥空间大、对密钥敏感、容易快速实现等特点,并能抵抗穷举攻击、已知明文攻击和唯密文攻击等。数值仿真结果验证了该算法的正确性和有效性。

英文摘要:

A symmetric image encryption algorithm that has a 128 bit key was proposed based on cellular neural network (CNN) and coupled map lattice (CML) model. Within the algorithm, a CNN that has a complex dynamical behavior and a piecewise linear chaotic map (PWLCM) were used to drive CML model as to quickly generate spatio-temporal chaotic sequences, which would be bitwise XORed with original image later. Algorithm analyses indicated that it has some excellent features such as a large key space, the sensitivity to the key, easily and quickly implementation, etc. Furthermore, the algorithm could resist the brute-force attacks, the know-plaintext attacks and ciphertext-only attacks. The computer simulations are carried out and the results show the correctness and effectiveness of the algorithm.

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