3 accepted papers
With the widespread application of machine learning-based graph classification models in fields such as biology and economics, there has been a growing number of attacks aimed at perturbing classification results. Although current defense methods, such as randomized smoothing, have achieved some suc…
Recently image steganography methods based on invertible neural networks (INNs) demonstrated the capability to automatically embed and extract secret messages while maintaining high visual quality in stego images. However, there remain concerns about security and invertibility of such methods. In th…
Steganography is a technique that hides secret messages into a public multimedia object without raising suspicion from third parties. However, most existing works cannot provide good robustness against lossy JPEG compression while maintaining a relatively large embedding capacity. This paper present…