23 citations · 38 across the 15 of their papers we have counts for
5 papers · 1 filter
What Breaks Embodied AI Security:LLM Vulnerabilities, CPS Flaws,or Something Else?
Boyang Ma, Hechuan Guo, Peizhuo Lv +5
Embodied AI systems (e.g., autonomous vehicles, service robots, and LLM-driven interactive agents) are rapidly transitioning from controlled environments to safety critical real-wo…
MARS: A Malignity-Aware Backdoor Defense in Federated Learning
Wei Wan, Yuxuan Ning, Zhicong Huang +7
Federated Learning (FL) is a distributed paradigm aimed at protecting participant data privacy by exchanging model parameters to achieve high-quality model training. However, this…
Spa-VLM: Stealthy Poisoning Attacks on RAG-based VLM
Lei Yu, Yechao Zhang, Ziqi Zhou +6
With the rapid development of the Vision-Language Model (VLM), significant progress has been made in Visual Question Answering (VQA) tasks. However, existing VLM often generate ina…
ECLIPSE: Expunging Clean-label Indiscriminate Poisons via Sparse Diffusion Purification
Xianlong Wang, Shengshan Hu, Yechao Zhang +5
Clean-label indiscriminate poisoning attacks add invisible perturbations to correctly labeled training images, thus dramatically reducing the generalization capability of the victi…
Robust Backdoor Detection for Deep Learning via Topological Evolution Dynamics
Xiaoxing Mo, Yechao Zhang, Leo Yu Zhang +5
A backdoor attack in deep learning inserts a hidden backdoor in the model to trigger malicious behavior upon specific input patterns. Existing detection approaches assume a metric…