A Multi-Layered Data Encryption and Decryption Scheme Based on Genetic Algorithm and Residual Numbers

Over the years, Steganography and Cryptography have been complementary techniques for enforcing security of digital data. The need for the development of robust multi-layered schemes to counter the exponential grow in the power of computing devices that can compromise security is critical in the design and implementation of security systems. Therefore, we propose a new combined steganographic and cryptographic scheme using the operators of genetic algorithm (GA) such selection, crossover and mutation, and some properties of the residue number system (RNS) with an appropriate fusing technique in order to embed encrypted text within images. The proposed scheme was tested using MatLab® R2017b and a CORE™i7 processor. Simulation results show that the proposed scheme can be deployed at one level with only the stego image containing the encrypted hidden message and at another level where the stego message is further encrypted. An analysis based on standard key metrics such as visual perception and statistical methods on steganalysis and cryptanalysis show that the proposed scheme is robust, is not complex with reduced runtime and will consume less power due to the use of residue numbers when compared to similar existing schemes.