.png){kind=icon}
.png){kind=icon}
Return
Image adaptive encryption algorithm using a novel 2D chaotic system
.png){kind=icon}
PRE
AI
DOI：10.1007/s11071-023-08397-8.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
In this paper, a universal two-dimensional (2D) enhanced cosine coupled model (2D-ECCM) is first designed, which can construct new 2D chaotic systems using most of the existing two one-dimensional (1D) maps as the seed maps. And a novel 2D Logistic-sine coupled map (2D-NLSCM) and a new 2D cubic-tent coupled map (2D-NCTCM) are generated by using the 2D-ECCM, and their chaotic features are analyzed by bifurcation diagram, trajectory, Lyapunov exponent spectrum, etc. Performance analyses show that two new maps have better chaotic behaviors than some state-of-the-art 2D chaos. Then, using the 2D-NLSCM, an image adaptive encryption algorithm is further designed. We propose an adaptive scrambling method to scramble image pixels directly by combining the target image information, and a bidirectional-sequential diffusion method for image pixels diffusion. The image adaptive scrambling can change the pixel values while effectively scrambling the pixel positions. And the bidirectional-sequential diffusion can be achieved to diffuse a minor change of a pixel value in the original image to all pixels of the encryption image. Therefore, the proposed algorithm is closely related to the target image in the encryption process. Moreover, the key of the proposed encryption algorithm is updated through the hash function SHA-512, which further increases the security of the algorithm. Ultimately, simulation experiment shows that the designed encryption algorithm has superior encryption efficiency. Performance analysis results indicate that the designed encryption algorithm, with average information entropy of 7.9988 and average chi-square of 238.3495, can withstand a series of common cryptanalytic attacks.
Keywords:
Chaos
Image encryption
2D-ECCM
Scrambling and diffusion
Performance analysis