A DNA Based Colour Image Encryption Scheme Using A Convolutional Autoencoder
Fawad Ahmed, Muneeb Ur Rehman, Jawad Ahmad, Muhammad Shahbaz Khan,, Wadii Boulila, Gautam Srivastava, Jerry Chun-Wei Lin, William J. Buchanan

TL;DR
This paper introduces a novel colour image encryption scheme that combines a convolutional autoencoder for dimensionality reduction with DNA and chaos-based encryption, improving speed and security for digital image transmission.
Contribution
It proposes a new autoencoder-based dimension reduction method combined with DNA and chaos encryption, enhancing efficiency and security of colour image encryption.
Findings
Autoencoder achieves 97% training accuracy and 95% validation accuracy.
The scheme successfully reconstructs original images with negligible perceptual distortion.
Encryption security is validated through multiple evaluation parameters.
Abstract
With the advancement in technology, digital images can easily be transmitted and stored over the Internet. Encryption is used to avoid illegal interception of digital images. Encrypting large-sized colour images in their original dimension generally results in low encryption/decryption speed along with exerting a burden on the limited bandwidth of the transmission channel. To address the aforementioned issues, a new encryption scheme for colour images employing convolutional autoencoder, DNA and chaos is presented in this paper. The proposed scheme has two main modules, the dimensionality conversion module using the proposed convolutional autoencoder, and the encryption/decryption module using DNA and chaos. The dimension of the input colour image is first reduced from N M 3 to P Q gray-scale image using the encoder. Encryption and decryption are then…
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