A multi-image compression and encryption scheme based on fractional chaotic map

Abstract

In this paper, a visual security encryption scheme for multi-color images based on BP neural network and fractional chaotic map is proposed, which disguises secret images as a meaningful visual image. Firstly, three color images are compressed based on BP neural network. Then, according to the pseudo-random sequence generated by fractional chaotic map, the merged compressed images are scrambled by spiral transformation and diffused by XOR, in which the direction and degree of spiral transformation can be adjusted. In order to ensure the visual effect of the camouflage image, the lifting wavelet transform (LWT) is used to decompose the carrier image to obtain the coefficient matrix, and the cipher images are adjusted to a narrow range and embedded into the coefficient matrixes based on the pseudo-random sequence. Finally, visually secure image can be generated by inverse lifting wavelet transform. The reverse algorithm can restore the images by extraction, decryption and decompression. Experimental results verify that the proposed scheme has feasibility, robustness, anti-noise and clipping capability, and the PSNR value is no less than 31.4 under various attacks.

Multiple-image encryption scheme based on a new 2D hyperchaotic map with blurred pixels

“…With the increasing amount of information on the network, researchers are focusing on multiple image encryption (MIE) algorithms [29][30][31][32]. Single image encryption algorithm cannot hide information into other images, which may lead to low security and efficiency [33,34].…”

Dynamics of a simple third-order autonomous MLC circuit

“…memristor, provides a new way to design simple chaotic circuits [8][9][10][11]. Complex dynamical characteristics of chaos make it convenient for chaos-based applications, especially in the field of image encryptions [12][13][14][15]. For the study of chaos, the bifurcation routes, time-sequence evolutions, and the motion on phase portraits etc are intuitive ways for the detailed investigation.…”