One of the most important issues in cyberspace and with the tremendous advancement in digital technology, are effective cryptographic techniques to protect the security and ownership of digital information that is exchanged through the Internet and communications. Encryption algorithms are divided into different categories, image, text, and audio encryption algorithms that have many applications in the field of security. Steganography is one of the methods of cryptography and is the art and science of putting secret messages in a cover message, in such a way that no one except the sender and receiver of the message doubts the existence of the secret message. Due to the wide range of applications in this field, there are various challenges such as increasing the quality of the output image and increasing the storage capacity and most importantly reducing the statistical anomalies of the output image to reduce the possibility of concealment. At present, due to the use of meta-heuristic algorithms such as ACO, PSO, GA and due to the good performance of these methods, steganography can be considered as a search and optimization problem whose main purpose is to increase the accuracy of methods based on The scope of the space is to hide the image, streamline the process of hiding and retrieving the image, and increase the cryptographic quality of the images. In this dissertation, a method to solve the problem of improving security along with increasing the accuracy of image encryption is presented, in which a new plan for information encryption using multi-objective gray wolf optimization (MO-GWO) algorithm in information exchange space is introduced. The multi-objective Gray Wolf Optimization Algorithm is a new meta-heuristic algorithm that starts with a set of random answers, then searches for the optimal solution in the problem space. The proposed method is implemented on the MATLAB simulator and the results are compared with the latest work done. The results show that the proposed algorithm has been able to achieve good performance in increasing accuracy compared to the GA method in the field of image steganography.
