Evolutionary-based image encryption using biomolecules and non-coupled map lattice. (August 2021)

• Record Type: Journal Article
• Authors: Abbasi, Ali Asghar; Mazinani, Mahdi; Hosseini, Rahil
• Is Part Of: Optics & laser technology. Volume 140(2021)
• Publication Date: 2021-08
• Subjects: Image encryption -- Chaos function -- Biomolecules -- ICA; Optics -- Periodicals; Lasers -- Periodicals; Electronic journals; 621.366
• DOI: 10.1016/j.optlastec.2021.106974
• Languages: English
• ISSNs: 0030-3992

Abstract

Highlight: Hidden key with SHA-256 is intended for initial value of non-coupled map lattice. Using the Chaotic Rate operator for permutation. Using DNA-XOR and RNA-Complement codon operators based on chaos for diffusion. Using the operators of the imperialist competition algorithm for pixels diffusion. Using evolutionary algorithm to increase entropy and reduce correlation coefficient. Abstract: Image encryption is an effective way of protecting multimedia data; it is done by transferring multimedia data into an undetectable format within the network context. In this paper, a new Chaotic Evolutionary Biomolecules Model (CEBM) based on the concepts of biological molecules (DNA and RNA) is presented for image encryption. The proposed model consists of four phases. In the first phase, a secret 256-bit key using the SHA-256 algorithm is assumed for the initial value of the non-coupled map lattice function. In the second phase, the Chaotic Rate operator is used for permutation. In the third phase, DNA XOR operators and RNA codons complement operator based on chaos are used for Diffusion. In the final phase, the steps taken 1, 2, and 3 are repeated by the number of the population of the early countries of Imperialist Competition Algorithm. The population is then optimized using imperialist competition algorithm operators. The results show the superiority of the proposed model over other models. In addition, the proposed model is highly resistant to common attacks and has an entropy value average of 7.99944.