摘要
为了解决混沌加密系统密钥空间设计上的不足以及数据加密标准(DES)加密算法易被攻击的问题,将细胞神经网络与DES加密算法相结合,提出一种混合加密通信方案.该方案利用细胞神经网络产生混沌信号,将其经过取整、取模、平方、开方、增益、偏移等运算处理后,用得到的新的混沌伪随机序列将图像加密,然后利用DES算法进行再加密.文中还讨论了系统的实现方法.仿真结果表明,采用此混合加密方案进行加解密均可取得较好的效果,解密结果对细胞神经网络初值和DES密钥高度敏感,安全性能有所提高.
In order to overcome the deficiency of the key space of chaotic encryption system and to protect the Data Encryption Standard （DES） algorithm from being attacked, this paper proposes a secure communication scheme for images by combining the cellular neural network （CNN） with DES algorithm. In the proposed scheme, the original chaotic signal generated by CNN is rounded, taken module, squared, extracted, magnified and excursed. After that, a new chaotic pseudo-random sequence is obtained and is used to encrypt the image. Then, the image is encrypted again with DES algorithm. The realization of the secure communication system is also discussed in this paper. Simulated results show that the proposed scheme is of good encryption and decryption efficiency and improves security performance, and that the decrypted results are highly sensitive to the initial condition of CNN and the key of DES. In addition, the traditional cryptanalysis is hardly useful for the proposed encryption system due to the random perturbation in hardware implementation.
出处
《华南理工大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2007年第9期31-35,共5页
Journal of South China University of Technology(Natural Science Edition)
基金
广东省自然科学基金资助项目(06026809
06025729)
关键词
图像
保密通信
细胞神经网络
混沌信号
图像加密
数据加密标准
image
secure communication
cellular neural network
chaotic signal
imageencryption
Data Encryption Standard
