This study introduces an effective framework for image encryption,leveraging the principles of chaos theory through the use of cellular automata neighborhood(CAN)and a novel two-dimensional hyperchaotic map(2D-SGHM)derived from the classic sine and Gauss maps.The core of our investigation delved into the basic performance and dynamical behaviors of this map.The findings reveal a wide hyperchaotic range characterized by large positive Lyapunov exponents,establishing map superiority in image encryption.By integrating different cellular automata neighborhoods,we can generate diverse image encryption schemes.Specifically,this study highlights three distinct image encryption algorithms constructed from one-dimensional,von Neumann and Moore neighborhoods,named OIEA,NIEA,and MIEA.Each scheme is uniquely designed to harness the benefits of CAN for encryption,thereby enhancing the overall effectiveness and security level of the image encryption process.In the experiment,the number of pixels change rates for OIEA,NIEA,and MIEA are 99.6097%,99.6092%,and 99.6098%,and the unified average changing intensities are 33.4603%,33.4626%,and 33.4628%,respectively.The correlation coefficients of the neighboring pixels are notably low,recorded at 0.00065,0.00064,and 0.00031 for each scheme,while the information entropies are nearly identical,with scores of 7.9977,7.9975,and 7.9976,showing that our encryption schemes have high security performance and can provide reliable security for different types of data information.
