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AgentTypo: Adaptive Typographic Prompt Injection Attacks against Black-box Multimodal Agents
Yanjie Li, Yiming Cao, Dong Wang +1
Multimodal agents built on large vision-language models (LVLMs) are increasingly deployed in open-world settings but remain highly vulnerable to prompt injection, especially throug…
Algorithmic Complexity Attacks on All Learned Cardinality Estimators: A Data-centric Approach
Yingze Li, Xianglong Liu, Dong Wang +4
Learned cardinality estimators show promise in query cardinality prediction, yet they universally exhibit fragility to training data drifts, posing risks for real-world deployment.…
Partitioning for Intrinsic Model Inversion Resistance in Collaborative Inference
Rongke Liu, Youwen Zhu, Lei Zhou +2
In collaborative inference (CI), transmitting intermediate representations from edge devices enables model inversion attacks (MIA) that reconstruct the original inputs , whi…
Gradient-Free Adversarial Purification with Diffusion Models
Xuelong Dai, Dong Wang, Xiuzhen Cheng +1
Adversarial training and adversarial purification are two widely used defense strategies for enhancing model robustness against adversarial attacks. However, adversarial training r…
How Breakable Is Privacy: Probing and Resisting Model Inversion Attacks in Collaborative Inference
Rongke Liu, Youwen Zhu, Dong Wang +3
Collaborative inference (CI) improves computational efficiency for edge devices by transmitting intermediate features to cloud models. However, this process inevitably exposes feat…