A Novel Image Encryption Algorithm Based on a Fractional-Order Hyperchaotic System and DNA Computing

Author:

Li Taiyong1234ORCID,Yang Minggao1,Wu Jiang1,Jing Xin1

Affiliation:

1. School of Economic Information Engineering, Southwestern University of Finance and Economics, 55 Guanghuacun Street, Chengdu 610074, China

2. Collaborative Innovation Center for the Innovation and Regulation of Internet-Based Finance, Southwestern University of Finance and Economics, 55 Guanghuacun Street, Chengdu 610074, China

3. Laboratory for Financial Intelligence and Financial Engineering, Southwestern University of Finance and Economics, 55 Guanghuacun Street, Chengdu 610074, China

4. Institute of Chinese Payment System, Southwestern University of Finance and Economics, 55 Guanghuacun Street, Chengdu 610074, China

Abstract

In the era of the Internet, image encryption plays an important role in information security. Chaotic systems and DNA operations have been proven to be powerful for image encryption. To further enhance the security of image, in this paper, we propose a novel algorithm that combines the fractional-order hyperchaotic Lorenz system and DNA computing (FOHCLDNA) for image encryption. Specifically, the algorithm consists of four parts: firstly, we use a fractional-order hyperchaotic Lorenz system to generate a pseudorandom sequence that will be utilized during the whole encryption process; secondly, a simple but effective diffusion scheme is performed to spread the little change in one pixel to all the other pixels; thirdly, the plain image is encoded by DNA rules and corresponding DNA operations are performed; finally, global permutation and 2D and 3D permutation are performed on pixels, bits, and acid bases. The extensive experimental results on eight publicly available testing images demonstrate that the encryption algorithm can achieve state-of-the-art performance in terms of security and robustness when compared with some existing methods, showing that the FOHCLDNA is promising for image encryption.

Funder

National Natural Science Foundation of China

Publisher

Hindawi Limited

Subject

Multidisciplinary,General Computer Science

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