Safeguarding the identity of people in photographs or videos published through social networks or television is of great importance to those who do not wish to be recognized. In this paper, a face detecting and coding system is designed with the goal of solving this problem. Mathematical models to generate chaotic orbits are deployed. One of them applies the diffusion technique to scramble the pixels of each face while another implements the confusion technique to alter the relation between plain text and ciphered text. Afterward, another two orbits are utilized for the steganography technique to modify the least significant bit (LSB) to conceal data that would allow authorized users to decipher the faces. To verify the robustness of the proposed encryption algorithm, different tests are performed with the Lena standard image, such as correlation diagrams, histograms, and entropy. In addition, occlusion, noise, and plain image attacks are performed. The results are compared with those of other works, and the proposed system provided high sensitivity at secret key and a large space for the encryption keys, good speed for ciphering, disorder in the cryptogram, security, data integrity, and robustness against different attacks.

In this article, a safe communication system is proposed that implements one or more portable devices denominated SBC (single-board computers), with which photographs are taken and that later utilizes the OpenCV Library for the detection and identification of the faces that appear in them. Subsequently, it consults the information in a stored database, whether locally in SBC or in a remote server, to verify that the faces should be coded, and it encrypts these, implementing a new cryptosystem that executes mathematical models to generate chaotic orbits, one of which is used for application on two occasions the technique of diffusion with the purpose of carrying out a small change in one of the pixels of the image, generating very different cryptograms. In addition, in order to make a safer system, it implements other chaotic orbits during the technique of confusion. With the purpose of verifying the robustness of the encryption algorithm, a statistical analysis is performed employing histograms, horizontal, vertical, and diagonal correlation diagrams, entropy, number of pixel change rate (NPCR), unified average change intensity (UACI), sensitivity of the key, encryption quality analysis, and the avalanche effect. The cryptosystem is very robust in that it generates highly disordered cryptograms, supports differential attacks, and in addition is highly sensitive to changes in the pixels as well as in the encrypted keys.