Image steganography based on pixel ranking and Particle Swarm Optimization

We propose a novel approach for image steganog-raphy by taking the advantages of Particle Swarm Optimization (PSO) and Least Significant Bits (LSBs) replacement. This technique is based on hiding the Most Significant Bits (MSBs) of secret image pixels in LSBs of a host image. The proposed method finds the best pixel in order to embed. We define four feature functions and four corresponding coefficients to rank the pixels. The features and the coefficients are defined based on the MSBs of host image. Our method defines a special secret key for each host image based on PSO in which, each particle represents a potential solution and we can evaluate all of them. This novelty causes better exploration of search space in order to find suitable pixel ranking and higher security. The experimental results show the superiority of this approach over the state-of-the-art methods.