7 papers
TI-StegoAlign: Channel-Guided Post-Training for Generative Text Steganography under Tokenization Inconsistency
Jiuan Zhou, Yuhao Xue, Yu Cheng +2
Generative text steganography enables LLM agents to exchange secret information through task-relevant messages. Yet most methods evaluate recovery on sender-side tokens, whereas th…
Benign in Isolation, Harmful in Composition: Security Risks in Agent Skill Ecosystems
Yi Xie, Jiawei Du, Yu Cheng +2
Skills are becoming the capability layer through which LLM agents turn plans into actions, but their use introduces security risks such as data leakage, unauthorized operations, an…
TAME: A Trustworthy Test-Time Evolution of Agent Memory with Systematic Benchmarking
Yu Cheng, Yongkang Hu, Jiuan Zhou +8
Test-time evolution of agent memory represents a pivotal paradigm for advancing AGI, as it strengthens complex reasoning through experience accumulation without requiring parameter…
Face-D(^2)CL: Multi-Domain Synergistic Representation with Dual Continual Learning for Facial DeepFake Detection
Yushuo Zhang, Yu Cheng, Yongkang Hu +4
Facial forgery techniques are advancing rapidly, posing severe threats to public trust and information security while imposing higher demands on the continual adaptation of DeepFak…
DTAMS: High-Capacity Generative Steganography via Dynamic Multi-Timestep Selection and Adaptive Deviation Mapping in Latent Diffusion
Yuhao Xue, Jiuan Zhou, Yu Cheng +1
With the rapid development of AIGC technologies, generative image steganography has attracted increasing attention due to its high imperceptibility and flexibility. However, existi…
RFNNS: Robust Fixed Neural Network Steganography with Universal Text-to-Image Models
Yu Cheng, Jiuan Zhou, Jiawei Chen +2
With the rapid development of generative AI, image steganography has garnered widespread attention due to its unique concealment. Recent studies have demonstrated the practical adv…