Title
Color image encryption using non-dominated sorting genetic algorithm with local chaotic search based 5D chaotic map
Abstract
The secure key generation is the predominant requirement of an image encryption. Chaotic maps are often considered by the researchers for secure key generation. However, chaotic maps suffer from hyper-tuning issue because the requirement of initial parameters. Therefore, an integrated non-dominated sorting genetic algorithm and local chaotic search based image encryption technique is proposed to tune the hyper-parameters of 5D chaotic map (TFCM). To implement TFCM, initially, the input image is decomposed into sub-bands using a dual-tree complex wavelet transform (DTCWT). These sub-bands are then diffused using the secret key obtained from the optimized 5D chaotic map. Finally, the inverse DTCWT is applied to obtain the final encrypted image. However, TFCM is computationally extensive for images with a larger size. Therefore, a parallel implementation of TFCM is also considered. Experimental analyses show that TFCM outperforms the competitive techniques in terms of NPCR, entropy, PSNR, and UACI by 0.9572%, 1.1576%, 1.0373%, and 1.0854%, respectively.
Year
DOI
Venue
2020
10.1016/j.future.2020.02.029
Future Generation Computer Systems
Keywords
DocType
Volume
Image encryption,Genetic algorithm,Chaotic maps,Hyper-parameter tuning
Journal
107
Issue
ISSN
Citations 
C
0167-739X
1
PageRank 
References 
Authors
0.36
0
4
Name
Order
Citations
PageRank
Manjit Kaur1238.41
Dilbag Singh26715.16
Kehui Sun38614.71
Umashankar Rawat493.27