An enhanced image encryption technique combining genetic algorithm and particle swarm optimization with chaotic function. Issue 9 (21st October 2021)

• Record Type: Journal Article
• Authors: Ferdush, Jannatul; Mondol, Greetashree; Prapti, Amrita Pritom; Begum, Mahbuba; Sheikh, Mohammad Nowsin Amin; Galib, Syed Md.
• Is Part Of: International journal of computers and applications. Volume 43:Issue 9(2021)
• Page Start: 960
• Page End: 967
• Publication Date: 2021-10-21
• Subjects: Image encryption -- chaotic map -- genetic algorithm -- particle swarm optimization; Computers -- Periodicals; Computer software -- Periodicals; Computer networks -- Periodicals; Multimedia systems -- Periodicals; Internet -- Periodicals; World Wide Web -- Periodicals; Minicomputers -- Periodicals; Microcomputers -- Periodicals; 004.05
• DOI: 10.1080/1206212X.2019.1662170
• Languages: English
• ISSNs: 1206-212X

Abstract

Abstract : Image encryption is a very common and attractive issue in digital image processing. Here, a combination of genetic algorithm and particle swarm optimization with a chaotic function model is proposed for image encryption. This paper uses the genetic algorithm for the enhanced encryption of pixel value and particle swarm optimization for improving the optimization process. The proposed method is divided into two parts. In the first stage, the plain RGB image is used for the initial population and then the genetic algorithm is applied to encrypt the image. In the next stage, the particle swarm optimization algorithm is applied for deciding the best-encrypted image. Next, the best image is re-encrypted until the best value is found. The double-point crossover is used for encryption. On the other hand, entropy is used as a fitness function for analyzing the fitness value. The obtained average entropy of the image is approximately 7.999, which is very close to the ideal value of entropy.