11 papers
Awakening the Hydra: Stabilizing Multi-Concept Backdoor Injection in Text-to-Image Diffusion Models
Kai Wang, Jiale Zhang, Chengcheng Zhu +2
Text-to-image diffusion models are increasingly developed through open-source reuse and repeated downstream fine-tuning, where reused checkpoints are difficult to verify and thus m…
Meta-FC: Meta-Learning with Feature Consistency for Robust and Generalizable Watermarking
Yuheng Li, Weitong Chen, Chengcheng Zhu +4
Deep learning-based watermarking has made remarkable progress in recent years. To achieve robustness against various distortions, current methods commonly adopt a training strategy…
Graph Federated Learning for Personalized Privacy Recommendation
Ce Na, Kai Yang, Dengzhao Fang +6
Federated recommendation systems (FedRecs) have gained significant attention for providing privacy-preserving recommendation services. However, existing FedRecs assume that all use…
BDFirewall: Towards Effective and Expeditiously Black-Box Backdoor Defense in MLaaS
Ye Li, Chengcheng Zhu, Yanchao Zhao +1
In this paper, we endeavor to address the challenges of backdoor attacks countermeasures in black-box scenarios, thereby fortifying the security of inference under MLaaS. We first…
Towards Generalized and Stealthy Watermarking for Generative Code Models
Haoxuan Li, Jiale Zhang, Xiaobing Sun +1
Generative code models (GCMs) significantly enhance development efficiency through automated code generation and code summarization. However, building and training these models req…
SPA: Towards More Stealth and Persistent Backdoor Attacks in Federated Learning
Chengcheng Zhu, Ye Li, Bosen Rao +3
Federated Learning (FL) has emerged as a leading paradigm for privacy-preserving distributed machine learning, yet the distributed nature of FL introduces unique security challenge…