A Bio-Inspired Image Encryption Algorithm Based on Chaotic Maps

Recently, several image cryptographic algorithms based on chaotic maps have been proposed. These algorithms differ in various aspects such as the type of chaotic maps used, methods used for confusion and diffusion, key size, and manipulating images as 2D or 3D. In this paper, a new image encryption algorithm based on chaotic maps is proposed. The algorithm is inspired by two bio-operations: crossover and mutation. Experimental results show that the proposed algorithm is capable of generating encrypted images with uniform distribution of the gray scale values and very low correlation coefficients of adjacent pixels, and is very sensitive to any change in the secret key values. We also compared the proposed algorithm run time and correlation coefficients for encrypted images with two other approaches.