TL;DR
PQ-TransSteg is introduced, a novel quantum-resilient image steganographic framework that integrates asymmetry-aware compression, post-quantum cryptography, and TransformerGAN for adaptive, high-capacity embedding.
Image steganography plays a crucial role in covert communication and copyright protection, but existing methods still struggle to achieve a balance between embedding capacity, image imperceptibility, anti-detection capabilities, and model complexity. Under complex channel interference such as compression and noise, the...
RIS-MoE is a robust and secure latent-space image steganography framework that integrates distortion-tolerant message representation with receiver-side adaptive latent restoration and consistently improves representative latent-space steganography pipelines as a plug-and-play restoration component, demonstrating its tr...
The proposed DeepSafe framework has potential applications in secure image communication, digital forensics, healthcare information protection, defense systems, cloud-based data sharing, and other privacy sensitive environments where secure handling of visual information is essential.
The proposed approach provides a unified, theoretically constrained, and scalable solution for secure high-capacity image steganography, and outperforms existing spatial, transform-domain, and deep learning-based methods.
This study presents a comprehensive analysis of steganography and steganalysis methods, evolving from classical to advanced intelligence frameworks by emphasizing image quality, security of hidden information, payload capacity, and robust detection mechanisms against adversarial perturbations.
The rapid expansion of wireless communication technologies, including the Internet of Things (IoT), cloud computing, and emerging 5G/6G networks, has intensified the demand for security frameworks capable of simultaneously protecting data confidentiality and concealing the existence of sensitive information. This revie...
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