activity
20192025
most citedShielding Federated Learning: Robust Aggregation with Adaptive Client Selection

50 citations · 132 across the 29 of their papers we have counts for

collaborators
Showing 2024Show all

7 papers · 1 filter

cs.CY2024★ 1 cited

BadRobot: Jailbreaking Embodied LLM Agents in the Physical World

Hangtao Zhang, Chenyu Zhu, Xianlong Wang +9

Embodied AI represents systems where AI is integrated into physical entities. Large Language Model (LLM), which exhibits powerful language understanding abilities, has been extensi…

cs.CR2024

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…

cs.CR2024★ 1 cited

Large Language Model Watermark Stealing With Mixed Integer Programming

Zhaoxi Zhang, Xiaomei Zhang, Yanjun Zhang +5

The Large Language Model (LLM) watermark is a newly emerging technique that shows promise in addressing concerns surrounding LLM copyright, monitoring AI-generated text, and preven…

cs.CR2024★ 1 cited

DarkFed: A Data-Free Backdoor Attack in Federated Learning

Minghui Li, Wei Wan, Yuxuan Ning +4

Federated learning (FL) has been demonstrated to be susceptible to backdoor attacks. However, existing academic studies on FL backdoor attacks rely on a high proportion of real cli…

cs.CV2024

Detector Collapse: Physical-World Backdooring Object Detection to Catastrophic Overload or Blindness in Autonomous Driving

Hangtao Zhang, Shengshan Hu, Yichen Wang +5

Object detection tasks, crucial in safety-critical systems like autonomous driving, focus on pinpointing object locations. These detectors are known to be susceptible to backdoor a…

cs.CV2024★ 2 cited

Securely Fine-tuning Pre-trained Encoders Against Adversarial Examples

Ziqi Zhou, Minghui Li, Wei Liu +7

With the evolution of self-supervised learning, the pre-training paradigm has emerged as a predominant solution within the deep learning landscape. Model providers furnish pre-trai…