LAUSR

Due to the increasing demand for IoMT applications in numerous fields such as healthcare, smart city, smart grids, industrial internet, etc. The privacy and security become a major issue in front of various researchers working in this field. This work proposed a lightweight image encryption algorithm based on a logistic-tent map and crossover operator of a genetic algorithm. Various 1-D chaotic maps are discussed in the literature review, but in some cases, hybrid 1-D chaotic maps have higher performance than simple 1-D chaotic maps. So 1-D chaotic map along with a crossover operator is used in this work. Here logistic-tent map and crossover are used to generate the random session key for each image encryption. Also, a crossover operator is used in encryption rounds for increasing confusion and diffusion. Here in this work, for each image encryption, a new intelligent session key is generated. The strength of the proposed image cryptographic scheme is assessed against resistance to the differential attack (UACI and NPCR), statistical attack (histogram analysis, correlation coefficient and information entropy) and sensitivity to the secret key. The extensive experiments of performance and security assessment show that the proposed cryptographic image scheme is secure enough to withstand all potential cryptanalytic attacks.