A coupled map lattice-based image encryption approach using DNA and bi-objective genetic algorithm
by Shelza Suri; Ritu Vijay
International Journal of Information and Computer Security (IJICS), Vol. 12, No. 2/3, 2020

Abstract: The paper presents a coupled map lattice (CML) and deoxyribonucleic acid (DNA)-based image encryption algorithm that uses genetic algorithm (GA) to get the optimised results. The algorithm uses the chaotic method CML and DNA to create an initial population of DNA masks in its first stage. The GA is applied in the second stage to obtain the best mask for encrypting the given plain image. The paper also discusses the use of two more chaotic functions, i.e., logistic map (LM) and transformed logistic map (TLM) with DNA-GA-based hybrid combination. The paper evaluates and compares the performance of the proposed CML-DNA-GA algorithm with LM-DNA-GA, TLM-DNA-GA hybrid approaches. The results show that the proposed approach performs better than the other two. It also discusses the impact of using a bi-objective GA optimisation for image encryption and applies the same to the all three discussed techniques. The results show that bi-objective optimisation of the proposed algorithm gives balanced results with respect to the selected fitness functions.

Online publication date: Fri, 14-Feb-2020

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