14 papers · 1 filter
WaveMark: Robust Wavelet-Domain Image Watermarking for Diffusion Models
Jie Cao, Qi Li, Chaklam Cheong +4
Image watermarking enables provenance tracing for photorealistic images generated by diffusion models. However, state-of-the-art (SOTA) removal attacks can suppress embedded signal…
SkillShield: Prompt-Space Security Skills for LLM Coding Agents
Xiaodong Wu, Zhimin Zhao, Qi Li +4
A coding agent edits files and executes shell commands with its developer's privileges, allowing malicious requests to translate directly into harmful actions or functional malware…
EVOMAL: Self-Poisoning in Self-Evolving Coding Agents
Xiaodong Wu, Yu Shi, Qi Li +5
Self-evolving LLM coding agents write their own tools by imitating retrieved skills from shared skill libraries. We identify a vulnerability in this loop: during authoring, a retri…
MarkNull: Model-Agnostic Watermark Removal in AI-Generated Images via On-Manifold Latent Manipulation
Jie Cao, Qi Li, Zelin Zhang +4
Digital watermarking has emerged as a critical technique for provenance and copyright attribution in AI-generated imagery, yet its robustness against realistic, model-agnostic remo…
Security, Privacy, and Ethical Risks in OpenClaw
Yutong Jin, Zelin Zhang, Zhijin Lyu +1
This paper systematically investigates the security, privacy, and ethical risks, as well as the traceability challenges of OpenClaw, a locally executable AI agent system for natura…
From AI-Generated Content to Agentic Action: Security and Safety Threats in Generative AI
Zelin Zhang, Qi Li, Jie Cao +2
Generative AI systems are increasingly used not only to produce content but also to retrieve data, invoke tools, and execute actions. This work examines the security and safety imp…
MarkSweep: A No-box Removal Attack on AI-Generated Image Watermarking via Noise Intensification and Frequency-aware Denoising
Jie Cao, Zelin Zhang, Qi Li +1
AI watermarking embeds invisible signals within images to provide provenance information and identify content as AI-generated. In this paper, we introduce MarkSweep, a novel waterm…
Secure and Robust Watermarking for AI-generated Images: A Comprehensive Survey
Jie Cao, Qi Li, Zelin Zhang +2
The rapid progress of Generative Artificial Intelligence (GenAI) has enabled the effortless synthesis of high-quality visual content, while simultaneously raising pressing concerns…
Robustness Assessment and Enhancement of Text Watermarking for Google's SynthID
Xia Han, Qi Li, Jianbing Ni +1
Recent advances in LLM watermarking methods such as SynthID-Text by Google DeepMind offer promising solutions for tracing the provenance of AI-generated text. However, our robustne…
When There Is No Decoder: Removing Watermarks from Stable Diffusion Models in a No-box Setting
Xiaodong Wu, Tianyi Tang, Xiangman Li +2
Watermarking has emerged as a promising solution to counter harmful or deceptive AI-generated content by embedding hidden identifiers that trace content origins. However, the robus…
SecureT2I: No More Unauthorized Manipulation on AI Generated Images from Prompts
Xiaodong Wu, Xiangman Li, Qi Li +2
Text-guided image manipulation with diffusion models enables flexible and precise editing based on prompts, but raises ethical and copyright concerns due to potential unauthorized…
PDLRecover: Privacy-preserving Decentralized Model Recovery with Machine Unlearning
Xiangman Li, Xiaodong Wu, Jianbing Ni +2
Decentralized learning is vulnerable to poison attacks, where malicious clients manipulate local updates to degrade global model performance. Existing defenses mainly detect and fi…
SoK: A Comprehensive Security Analysis of Jailbreak Resilience in GPT and DeepSeek Models
Xiaodong Wu, Xiangman Li, Qi Li +2
The rapid proliferation of Large Language Models (LLMs) has heightened concerns regarding their exposure to jailbreak attacks, which craft adversarial inputs designed to elicit uns…
Robustness of Watermarking on Text-to-Image Diffusion Models
Xiaodong Wu, Xiangman Li, Jianbing Ni
Watermarking has become one of promising techniques to not only aid in identifying AI-generated images but also serve as a deterrent against the unethical use of these models. Howe…