Image Encryption by Using ACGLML


Thèse de Doctorat, 2021

130 Pages


Résumé ou Introduction

In the present-day era of typical social media communications, it is vital that privacy is to be preserved due to attacks on multimedia data through various methods. It is well known that the encryption standards either lack in keyspace or poor encryption strength. Hence, it is proposed to use a novel method in which both keyspace and encryption are increased.

Discrete cosine transforms (DCT) of the image are encrypted using a generalized logistic equation. Due to this idea, both compression and encryption are done simultaneously. Before applying DCT, the image is shuffled using Arnold Cat Map. The proposed compression and encryption method is validated using several chaotic metrics such as; Bifurcation diagram, Mutual information, Kolmogorov Sinai Entropy density, Kolmogorov Sinai Entropy generality, Space-Amplitude diagram, Space-Time diagram. Intruders are discouraged through the improved metrics such as NPCR (Number of Pixels changing rate), UACI (Unified Averaged changed intensity), and mutual information among the lattices used as the key.

In the same way, image reconstruction quality is improved and verified through the metrics such as PSNR (Peak Signal to noise ratio) and FOM (Figure of Merit). Compression performance is evaluated through the metric CR (Compression ratio). The performance is evaluated for both gray and color image databases under a noisy channel environment.

Résumé des informations

Titre
Image Encryption by Using ACGLML
Auteur
Année
2021
Pages
130
N° de catalogue
V1022972
ISBN (ebook)
9783346433381
ISBN (Livre)
9783346433398
Langue
anglais
Mots clés
ACGLML
Citation du texte
Dr. Pradheep Manisekaran (Auteur), 2021, Image Encryption by Using ACGLML, Munich, GRIN Verlag, https://www.grin.com/document/1022972

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