Combining improved genetic algorithm and matrix semi-tensor product (STP) in color image encryption

TitleCombining improved genetic algorithm and matrix semi-tensor product (STP) in color image encryption
Publication TypeJournal Article
Year of Publication2021
AuthorsX Chai, X Zhi, Z Gan, Y Zhang, Y Chen, and J Fu
JournalSignal Processing
Volume183
Date Published06/2021
Abstract

Image encryption is one of the important methods for preservation of confidentiality and integrity of digital images. In this paper, a color image cryptosystem based on improved genetic algorithm and matrix semi-tensor product (STP) is introduced. The encryption process is composed of five stages, preprocessing, DNA encoding, crossover, mutation and DNA decoding. Firstly, the color plain image is splitted into its red, green and blue components, and they are preprocessed by an adaptive block-based image preprocessing driven by semi-tensor product (ABPSTP) to get new components. Next, the obtained components are converted to DNA sequences according to DNA encoding rules. Subsequently, the resulting sequences are shuffled by a double crossover operation of inter-intra components (DCOIC), and diffused by a DNA complementary cycle mutation strategy (DCCMS). Finally, the cipher image is obtained by decoding the diffused DNA components and recombining them. The selection of crossover components and determination of intersection points are controlled by plain image information and chaotic sequences, the mutation position and mutation rule of the element are dependable on them, thus our algorithm may withstand known-plaintext and chosen-plaintext attacks effectively. Simulation results demonstrate that our cipher has large key space, high key sensitivity, and it may resist various attacks.

DOI10.1016/j.sigpro.2021.108041
Short TitleSignal Processing