A Color Image Encryption Method Based on Dynamic Selection Chaotic System and Singular Value Decomposition

Mengyao Li, Xianwen Fang () and Asimeng Ernest
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Mengyao Li: School of Mathematics and Big Data, Anhui University of Science and Technology, Huainan 232001, China
Xianwen Fang: School of Mathematics and Big Data, Anhui University of Science and Technology, Huainan 232001, China
Asimeng Ernest: Department of Computer Science and Telecommunication, Jiangsu University, Zhenjiang 212013, China

Mathematics, 2023, vol. 11, issue 15, 1-27

Abstract: As the basis for guiding business process decisions, flowcharts contain sensitive information pertaining to process-related concepts. Therefore, it is necessary to encrypt them to protect the privacy or security of stakeholders. Using the principles of image singular value decomposition, chaotic system randomness, and neural network camouflage, a business flow chart encryption method based on dynamic selection chaotic system and singular value decomposition is proposed. Specifically, a dynamic selected chaotic system is constructed based on the nonlinear combination of one-dimensional chaotic system Logistics and Sine, and its randomness is verified. Next, using the neural network, the process image is merged into a gray matrix. The double-bit unitary matrix scrambling based on singular value decomposition is then proposed. Subsequently, using the dynamic selected chaotic system, a new sub-division diffusion method is proposed, which combines, diffuses, and performs weighted superposition to generate a matrix after diffusion and compression. Finally, the asymmetric encryption method encrypts the color image and reduces its dimensionality into a single grayscale ciphertext, and the decryption process is not the reverse of the encryption process. Simulation results and performance analysis show that the proposed image encryption scheme has good encryption performance.

Keywords: business process diagram; image encryption; chaotic systems; neural network; singular value decomposition (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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