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2024 | OriginalPaper | Buchkapitel

Combination of an Improved Feistel Scheme and Genetic Operators for Chaotic Image Encryption

verfasst von : Hicham Rrghout, Mourad Kattass, Mariem Jarjar, Naima Benazzi, Younes Qobbi, Abdellatif Jarjar, Abdelhamid Benazzi

Erschienen in: Computing, Internet of Things and Data Analytics

Verlag: Springer Nature Switzerland

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Abstract

In this work, we will propose a new color image encryption technique using chaotic maps and based on an improved Feistel scheme. This scheme is reinforced by two genetic operators adapted to cryptography. After putting the original image into a single vector, a genetic mutation is applied. Then, a subdivision into sub-blocks of pseudo-random size is performed. Feistel's technique is applied using new confusion and diffusion functions. A genetic crossover is installed at the output and is controlled by a pseudo-random crossover table. Simulations carried out on a large sample of images of various sizes demonstrate that our method is resilient against all known attacks.

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Vorheriges Kapitel A Comparative Study of Deep Learning Loss Functions: A Polyp Segmentation Case Study

Nächstes Kapitel Post-processing of Closed Contours to Obtain Inscribed K-Sided Polygons

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Titel: Combination of an Improved Feistel Scheme and Genetic Operators for Chaotic Image Encryption
verfasst von: Hicham Rrghout
Mourad Kattass
Mariem Jarjar
Naima Benazzi
Younes Qobbi
Abdellatif Jarjar
Abdelhamid Benazzi
Verlag: Springer Nature Switzerland
Buch: Computing, Internet of Things and Data Analytics
Print ISBN: 978-3-031-53716-5

Electronic ISBN: 978-3-031-53717-2

Copyright-Jahr: 2024
DOI: https://doi.org/10.1007/978-3-031-53717-2_8

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