Grayscale image encryption based on Latin square and cellular neural network
Min Lin, Fei Long, Lu Guo · 2016
In this paper, we propose a grayscale image encryption scheme based on Latin square and cellular neural network. Initially, the original image is substituted by bitwise exclusive OR operation with an encrypted matrix, which is produced by a Latin square of order 256 and two chaotic sequences generated from CNN. Next, the substituted image is decomposed into several blocks, which are scrambled by four different Latin squares of order 32. For each block, the selection of which Latin square depends on the remaining two chaotic sequences and the pixel mean value of each block. Finally, after scrambling the rows and columns of each block, we can obtain the encrypted image. The proposed scheme exhibits the features of large key space, high key sensitivity, low pixels correlation and high entropy. Simulation results demonstrate the feasibility and effectiveness of the proposed scheme.