Image Encryption Using the TLBO Algorithm and Image Hash
M. Abedzadeh, M. J. Rostami · Transactions on Machine Intelligence · 2021
An effective encryption algorithm must not only provide fast encryption but also be resistant to various attacks. Chaotic mappings are widely used in image encryption. Furthermore, since the hash of an image produces a distinct output for each image and changes drastically with even a single bit alteration, it can be an ideal candidate for the initial values in chaotic mappings. This paper explores the encryption of images inspired by the Teaching-Learning-Based Optimization (TLBO) algorithm, which is a metaheuristic algorithm. Initially, the image hash is computed using the SHA-512 hash function, and numbers between 0 and 1 are generated based on the obtained hash. The image is then divided into 16 equal parts. In the next step, the pixels of the image are permuted using a specific variant of the standard map proposed in this paper. In each iteration, the part with the best entropy is selected as the teacher. Among the generated values, the one that improves the entropy of that part is chosen, and other parts follow this value. Finally, the pixels of each part are altered using the logistic map. This algorithm offers both adequate execution time and high security.