文献类型：会议论文

英文题名：CNN-based Color Image Encryption Algorithm using DNA Sequence Operations

作者：Wang, Jingshuai Long, Fei Ou, Weihua

第一作者：Wang, Jingshuai

通信作者：Ou, WH[1]

机构：[1]Guizhou Inst Technol, Sch Elect Engn, Guiyang, Guizhou, Peoples R China;[2]Guizhou Univ, Coll Big Data & Informat Engn, Guiyang, Guizhou, Peoples R China;[3]Guizhou Normal Univ, Sch Big Data & Comp Sci, Guiyang, Guizhou, Peoples R China

第一机构：贵州理工学院

通信机构：corresponding author), Guizhou Normal Univ, Sch Big Data & Comp Sci, Guiyang, Guizhou, Peoples R China.

会议论文集：International Conference on Security, Pattern Analysis, and Cybernetics (ICSPAC)

会议日期：DEC 15-17, 2017

会议地点：Shenzhen, PEOPLES R CHINA

语种：英文

外文关键词：Color image encryption; cellular neural network; DNA operation; security analysis

年份：2017

摘要：The encryption algorithm of color images based on chaos theory has attracted lots of attentions in recent years. Nevertheless, due to the defects of the low dimensional chaotic system in single structure and small key space size, the security of cryptosystem is not sufficient enough. In this paper, we proposed a novel encryption algorithm for color images based on Deoxyribonucleic acid (DNA) sequence operations and cellular neural network (CNN) to dispose of these defects. The proposed cryptosystem of this paper takes on the features of large key space and complex structure. Firstly, the plain color image is split into three matrices (R, G, B) which are transformed into DNA matrices by the DNA encoding rules, respectively. Secondly, the elements' positions of the three DNA sequence matrices are scrambled via the chaotic sequences generated by CNN. Thirdly, the three DNA matrices are summed according to the certain rules and complemented by the complementary rules, and then the cipher-image is obtained by the DNA decoding rules via the DNA matrices. Simulation results and security analysis show that the encryption effect of this paper is not only better than traditional encryption algorithms but also has excellent ability to hold back familiar attacks.