文献类型：期刊文献

英文题名：An efficient self-adaptive model for chaotic image encryption algorithm

作者：Huang, Xiaoling[1];Ye, Guodong[2]

机构：[1]Guangdong Ocean Univ, Coll Sci, Zhanjiang 524088, Guangdong, Peoples R China;[2]City Univ Hong Kong, Dept Elect Engn, Kowloon Tong, Hong Kong, Peoples R China

年份：2014

卷号：19

期号：12

起止页码：4094

外文期刊名：COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION

收录：SCI-EXPANDED(收录号：WOS:000338822700005)、、EI(收录号：20142417814266)、Scopus(收录号：2-s2.0-84901932111)、WOS

基金：The work described in this paper was fully supported by the National Natural Science Foundation of China (No. 11301091), the Natural Science Foundation of Guangdong Ocean University of China (No. C13455), and the Foundation for Distinguished Young Talents in Higher Education of Guangdong Province of China (No. 2013LYM0037).

语种：英文

外文关键词：Encryption algorithm; Self-adaptive method; Permutation; Chaotic systems

外文摘要：In this paper, an efficient self-adaptive model for chaotic image encryption algorithm is proposed. With the help of the classical structure of permutation-diffusion and double simple two-dimensional chaotic systems, an efficient and fast encryption algorithm is designed. However, different from most of the existing methods which are found insecure upon chosen-plaintext or known-plaintext attack in the process of permutation or diffusion, the keystream generated in both operations of our method is dependent on the plain-image. Therefore, different plain-images will have different keystreams in both processes even just only a bit is changed in the plain-image. This design can solve the problem of fixed chaotic sequence produced by the same initial conditions but for different images. Moreover, the operation speed is high because complex mathematical methods, such as Runge-Kutta method, of solving the high-dimensional partial differential equations are avoided. Numerical experiments show that the proposed self-adaptive method can well resist against chosen-plaintext and known-plaintext attacks, and has high security and efficiency. (C) 2014 Elsevier B.V. All rights reserved.