Rethinking Security of Diffusion-Based Generative Steganography

Generative image steganography is a technique that conceals secret messages within generated images, without relying on pre-existing cover images. Recently, a number of diffusion model-based generative image steganography DM-GIS methods have been introduced, which effectively combat traditional...

T2I-Based Physical-World Appearance Attack against Traffic Sign Recognition Systems in Autonomous Driving

Traffic Sign Recognition TSR systems play a critical role in Autonomous Driving AD systems, enabling real-time detection of road signs, such as STOP and speed limit signs. While these systems are increasingly integrated into commercial vehicles, recent research has exposed their vulnerability to...

Diffusion-Based Task-Oriented Semantic Communications with Model Inversion Attack

Semantic communication has emerged as a promising neural network-based system design for 6G networks. Task-oriented semantic communication is a novel paradigm whose core goal is to efficiently complete specific tasks by transmitting semantic information, optimizing communication efficiency and ta...

DiffUMI: Training-Free Universal Model Inversion Via Unconditional Diffusion for Face Recognition

Face recognition technology presents serious privacy risks due to its reliance on sensitive and immutable biometric data. To address these concerns, such systems typically convert raw facial images into embeddings, which are traditionally viewed as privacy-preserving. However, model inversion...