Abstract

In this paper, a novel grayscale image cryptosystem based on hybrid chaotic maps is proposed. The scheme employs both confusion phase to scramble the location of pixels and diffusion phase for changing the content of pixels in consecutive manner. In this scheme, Arnold’s cat map is introduced to perform confusion operation and the principle of diffusion is achieved by using the proper selection of combined Sine map, Logistic map, and Tent map. Furthermore, exclusive OR (XOR), exchange, and transform operations are used to enhance the efficiency of diffusion phase. Accordingly, the use of chaotic maps and XOR operation provides a dual layer of security. Depending on the average absolute value of horizontal, vertical, and diagonal correlation coefficient of plain image as well as bifurcation properties of chaotic maps, one of the mentioned chaotic maps is selected for diffusion phase. First, original gray scale image matrix is extended to square matrix by adding the sequences generated with proper chaotic maps to implement the first step of diffusion phase. Then the Arnold’s cat map changes pixels location of new extended matrix by means of certain equation as confusion phase. The encrypted image is generated after applying XOR, exchange and transform operations on the content of pixels as second step of diffusion phase. Thus the system is able to build several more complicated chaotic structures. In addition the encryption and decryption processing time directly depend on the value of correlation coefficient of original image. Plain images with less correlation coefficient have less encryption and decryption processing time, and vice versa. Compared with several existing methods, the proposed scheme has more better properties, including wider chaotic ranges and more complex chaotic behavior. Experimental results show that the proposed system has proper encryption and decryption processing time, unified average changing intensity (UACI), number of pixel change rate (NPCR), and extensive security analysis for kind of images.

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