Steganographic Cryptosystem Based on the Use of Chaos Theory and Cellular Automata

The exchange of large amounts of information through public channels has become an everyday occurrence, a situation that generates great risks in the case of possible cyber-attacks and motivates the academic and scientific community to develop new robust security schemes. The objective of the research was to use mathematical and artificial intelligence tools to propose new security schemes. The design and implementation of a crypto-steganographic algorithm for text is described below. The methodology employed consisted of using cellular automata to detect the edges of a carrier image, leveraging the color contrast diversity, and the Tinkerbell chaotic attractor to generate two pseudo-random sequences: one for the encryption scheme and the other to select the edge pixels of the carrier image where cryptogram bits are hidden. Additionally, a verification phase was included in which the receiver provides a code to confirm that the stegoimage was not altered. The system key is shared between the sender and the receiver using the Diffie-Hellman algorithm. The proposed algorithm was subjected to a series of steganographic and cryptographic performance tests, including entropy analysis, mean square error (MSE), correlation coefficients, key sensitivity, peak signal-to-noise ratio (PSNR), normalized root mean square error (NRMSE), and the structural similarity index (SSI). The results of PSNR, MSE and SSI test were compared with scientific benchmarks, revealing indicators that align with the standards of information security. Finally, a crypto-steganographic algorithm was consolidated as a result of an academic exercise whose indicators make it potentially applicable in real-world contexts.