A Novel Image Encryption Model Based on Hybridization of Genetic Algorithm, Chaos Theory and Lattice Map

Abstract

Encryption is an important issue in information security which is usually provided using a reversible mathematical model. Digital image as a most frequently used digital product needs special encryption algorithms. This paper presents a new encryption algorithm high security for digital gray images using genetic algorithm and Lattice Map function. At the first the initial value of Logistic Map function from a 120 bits key is offered, and then by using the produced chaos series moves original picture pixels. In third step, the original image with Lattice Map function series create by sequence of Logistic Map function from latest level to encrypt the image. This process goes under evolution through the generation of the genetic algorithm until the algorithm converges to an encrypted image with a highest entropy and lowest correlation coefficient among pixels. The results reveal the highest level of resistance and security against statistical attacks. With obtained entropy results from the proposed method were 7.9993 which shows its proficiency compared to the counterpart methods.