The current research work proposed a novel optimization-based 2D-SIMM(Two-Dimensional Sine Iterative chaotic map with infinite collapse Mod-ulation Map)model for image encryption.The proposed 2D-SIMM model is derived o...The current research work proposed a novel optimization-based 2D-SIMM(Two-Dimensional Sine Iterative chaotic map with infinite collapse Mod-ulation Map)model for image encryption.The proposed 2D-SIMM model is derived out of sine map and Iterative Chaotic Map with Infinite Collapse(ICMIC).In this technique,scrambling effect is achieved with the help of Chaotic Shift Transform(CST).Chaotic Shift Transform is used to change the value of pixels in the input image while the substituted value is cyclically shifted according to the chaotic sequence generated by 2D-SIMM model.These chaotic sequences,generated using 2D-SIMM model,are sensitive to initial conditions.In the proposed algorithm,these initial conditions are optimized using JAYA optimization algorithm.Correlation coefficient and entropy are considered asfitness functions in this study to evaluate the best solution for initial conditions.The simulation results clearly shows that the proposed algorithm achieved a better performance over existing algorithms.In addition,the VLSI implementation of the proposed algorithm was also carried out using Xilinx system generator.With optimization,the correlation coefficient was-0.014096 and without optimization,it was 0.002585.展开更多
文摘The current research work proposed a novel optimization-based 2D-SIMM(Two-Dimensional Sine Iterative chaotic map with infinite collapse Mod-ulation Map)model for image encryption.The proposed 2D-SIMM model is derived out of sine map and Iterative Chaotic Map with Infinite Collapse(ICMIC).In this technique,scrambling effect is achieved with the help of Chaotic Shift Transform(CST).Chaotic Shift Transform is used to change the value of pixels in the input image while the substituted value is cyclically shifted according to the chaotic sequence generated by 2D-SIMM model.These chaotic sequences,generated using 2D-SIMM model,are sensitive to initial conditions.In the proposed algorithm,these initial conditions are optimized using JAYA optimization algorithm.Correlation coefficient and entropy are considered asfitness functions in this study to evaluate the best solution for initial conditions.The simulation results clearly shows that the proposed algorithm achieved a better performance over existing algorithms.In addition,the VLSI implementation of the proposed algorithm was also carried out using Xilinx system generator.With optimization,the correlation coefficient was-0.014096 and without optimization,it was 0.002585.
