@Article{cmc.2026.085806,
AUTHOR = {Rania Al-Ali, Mustafa Al-Fayoumi, Saleem Alsaraireh},
TITLE = {Cylinder XOR-Cascade: Lightweight Image Encryption Using Autoencoder-Based Representation},
JOURNAL = {Computers, Materials \& Continua},
VOLUME = {},
YEAR = {},
NUMBER = {},
PAGES = {{pages}},
URL = {http://www.techscience.com/cmc/online/detail/28116},
ISSN = {1546-2226},
ABSTRACT = {The rapid growth of the Internet of Things (IoT) and edge computing has increased the demand for secure and lightweight image encryption suitable for resource-constrained environments. This paper proposes a hybrid framework combining a residual-based pretrained autoencoder with a novel Cylinder XOR-Cascade (CXC) encryption scheme. The autoencoder compresses images into a compact latent representation while a residual branch preserves fine spatial details for accurate reconstruction. Both representations are encrypted using CXC, a two-pass column-wise stream cipher that enhances confusion and diffusion through sequential SHA3-256-based chaining and a cylinder-like feedback mechanism. Experiments on the USC-SIPI dataset demonstrate strong statistical security: Number of Pixels Change Rate (NPCR) <math id="mml-ieqn-1"><mo>≈</mo></math>99.5%, Unified Average Changing Intensity (UACI) <math id="mml-ieqn-2"><mo>≈</mo></math>33.5%, and entropy <math id="mml-ieqn-3"><mo>≈</mo></math>7.5. The full pipeline processes images in 280 ms on GPU and 928 ms on CPU, with the cryptographic stage requiring only 25 ms. For noisy channels, integrating Reed–Solomon forward error correction restores Structural Similarity Index Measure (SSIM) <math id="mml-ieqn-4"><mo>&gt;</mo></math>0.85 under Gaussian noise (<math id="mml-ieqn-5"><mi>σ</mi><mo>=</mo><mn>20</mn></math>), making the framework suitable for edge-assisted IoT and real-time visual transmission across both reliable and noisy channel conditions.},
DOI = {10.32604/cmc.2026.085806}
}