6 accepted papers
The rapid advancement of image-generation technologies has made it possible for anyone to create photorealistic images using generative models, raising significant security concerns. To mitigate malicious use, tracing the origin of such images is essential. Reconstruction-based attribution methods o
Messages embedded in diffusion generation noise suffer from severe attenuation due to denoising and VAE decoding, creating a persistent capacity–robustness trade-off. Identifying that extraction accuracy strictly correlates with the distance between candidate hypothesis images, we propose ASIR, a tr…
Recent advancements in video generation technologies have been significant, resulting in their widespread application across multiple domains. However, concerns have been mounting over the potential misuse of generated content. Tracing the origin of generated videos has become crucial to mitigate po
Due to the steganography of hiding images requires that the secret message be a full-size image, to improve the universality of steganography and decoding accuracy than hiding images, this paper presents image steganography with the deep orthogonal fusion of multi-scale channel attention (SOFMC). To…
Nowadays, social media has become the preferred communication platform for web users but brought security threats. Linguistic steganography hides secret data into text and sends it to the intended recipient to realize covert communication. Compared to edit-based linguistic steganography, generation-…
With the development of social networks, traditional covert communication requires more consideration of lossy processes of Social Network Platforms (SNPs), which is called robust steganography. Since JPEG compression is a universal processing of SNPs, a method using repeated JPEG compression to fit…