A CHAOS-BASED HYBRID IMAGE ENCRYPTION SCHEME USING DNA ENCODING AND DEEP NEURAL NETWORK KEY GENERATION

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Main Author: alsaadi, lamis alsaadi
Format: Recurso digital
Language:English
Published: Zenodo 2025
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author alsaadi, lamis alsaadi
author_facet alsaadi, lamis alsaadi
contents <p>This repository contains the preprint of the research article entitled <em>“A chaos-based hybrid image encryption scheme using DNA encoding and deep neural network key generation.”</em></p> <p>The study proposes a novel hybrid image encryption framework that integrates convolutional neural networks (CNNs) for plaintext-dependent dynamic key generation, a two-dimensional hyper-chaotic map for pixel permutation and diffusion, and dynamic DNA encoding for bit-level confusion. Unlike conventional chaos-based or DNA-based encryption schemes, the proposed method forms a fully coupled, adaptive architecture in which the plaintext image directly influences the cryptographic key stream and subsequent encryption stages.</p> <p>Extensive experimental evaluations on standard benchmark images demonstrate near-ideal cryptographic performance in terms of information entropy, differential attack resistance (NPCR and UACI), pixel correlation, key sensitivity, and robustness against noise and data loss.</p> <p>This version is a preprint and has been submitted to <em>PLOS ONE</em> for peer review. The content may be updated following the review process.</p>
format Recurso digital
id zenodo_https___doi_org_10_5281_zenodo_17936061
institution Zenodo
language eng
publishDate 2025
publisher Zenodo
record_format zenodo
spellingShingle A CHAOS-BASED HYBRID IMAGE ENCRYPTION SCHEME USING DNA ENCODING AND DEEP NEURAL NETWORK KEY GENERATION
alsaadi, lamis alsaadi
image encryption, chaos theory, DNA encoding, deep neural networks, hyper-chaotic systems, cryptography, information security, CNN-based key generation
image encryption
chaos theory
DNA encoding
deep neural networks
hyper-chaotic systems
cryptography
information security
CNN-based key generation
<p>This repository contains the preprint of the research article entitled <em>“A chaos-based hybrid image encryption scheme using DNA encoding and deep neural network key generation.”</em></p> <p>The study proposes a novel hybrid image encryption framework that integrates convolutional neural networks (CNNs) for plaintext-dependent dynamic key generation, a two-dimensional hyper-chaotic map for pixel permutation and diffusion, and dynamic DNA encoding for bit-level confusion. Unlike conventional chaos-based or DNA-based encryption schemes, the proposed method forms a fully coupled, adaptive architecture in which the plaintext image directly influences the cryptographic key stream and subsequent encryption stages.</p> <p>Extensive experimental evaluations on standard benchmark images demonstrate near-ideal cryptographic performance in terms of information entropy, differential attack resistance (NPCR and UACI), pixel correlation, key sensitivity, and robustness against noise and data loss.</p> <p>This version is a preprint and has been submitted to <em>PLOS ONE</em> for peer review. The content may be updated following the review process.</p>
title A CHAOS-BASED HYBRID IMAGE ENCRYPTION SCHEME USING DNA ENCODING AND DEEP NEURAL NETWORK KEY GENERATION
topic image encryption, chaos theory, DNA encoding, deep neural networks, hyper-chaotic systems, cryptography, information security, CNN-based key generation
image encryption
chaos theory
DNA encoding
deep neural networks
hyper-chaotic systems
cryptography
information security
CNN-based key generation
url https://doi.org/10.5281/zenodo.17936061