An efficient image encryption using non-dominated sorting genetic algorithm-III based 4-D chaotic maps Image encryption

Chaotic maps are extensively utilized in the field of image encryption to generate secret keys. However, these maps suffer from hyper-parameters tuning issues. These parameters are generally selected on hit and trial basis. However, inappropriate selection of these parameters may reduce the performa...

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Vydáno v:Journal of ambient intelligence and humanized computing Ročník 11; číslo 3; s. 1309 - 1324
Hlavní autoři: Gupta, Anvita, Singh, Dilbag, Kaur, Manjit
Médium: Journal Article
Jazyk:angličtina
Vydáno: Berlin/Heidelberg Springer Berlin Heidelberg 01.03.2020
Témata:
Artificial Intelligence
Computational Intelligence
Engineering
Original Research
Robotics and Automation
User Interfaces and Human Computer Interaction
Security evaluation
Image encryption
4-D chaotic map
NSGA-III
ISSN:1868-5137, 1868-5145
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Popis
Shrnutí:Chaotic maps are extensively utilized in the field of image encryption to generate secret keys. However, these maps suffer from hyper-parameters tuning issues. These parameters are generally selected on hit and trial basis. However, inappropriate selection of these parameters may reduce the performance of chaotic maps. Also, these hyper-parameters are not sensitive to input images. Therefore, in this paper, to handle these issues, a non-dominated sorting genetic algorithm-III (NSGA) based 4-D chaotic map is designed. Additionally, to improve the computational speed of the proposed approach, we have designed a novel master-slave model for image encryption. Initially, computationally expensive operations such as mutation and crossover of NSGA-III are identified. Thereafter, NSGA-III parameters are split among two jobs, i.e., master and slave jobs. For communication between master and slave nodes, the message passing interface is used. Extensive experimental results reveal that the proposed image encryption technique outperforms the existing techniques in terms of various performance measures.
ISSN:1868-5137
1868-5145
DOI:10.1007/s12652-019-01493-x