35 citations · 56 across the 42 of their papers we have counts for
9 papers · 1 filter
TEAR: Temporal-aware Automated Red-teaming for Text-to-Video Models
Jiaming He, Guanyu Hou, Hongwei Li +6
Text-to-Video (T2V) models are capable of synthesizing high-quality, temporally coherent dynamic video content, but the diverse generation also inherently introduces critical safet…
Hidden Tail: Adversarial Image Causing Stealthy Resource Consumption in Vision-Language Models
Rui Zhang, Zihan Wang, Tianli Yang +5
Vision-Language Models (VLMs) are increasingly deployed in real-world applications, but their high inference cost makes them vulnerable to resource consumption attacks. Prior attac…
ConfGuard: A Simple and Effective Backdoor Detection for Large Language Models
Zihan Wang, Rui Zhang, Hongwei Li +4
Backdoor attacks pose a significant threat to Large Language Models (LLMs), where adversaries can embed hidden triggers to manipulate LLM's outputs. Most existing defense methods,…
BadSR: Stealthy Label Backdoor Attacks on Image Super-Resolution
Ji Guo, Xiaolei Wen, Wenbo Jiang +3
With the widespread application of super-resolution (SR) in various fields, researchers have begun to investigate its security. Previous studies have demonstrated that SR models ca…
FIGhost: Fluorescent Ink-based Stealthy and Flexible Backdoor Attacks on Physical Traffic Sign Recognition
Shuai Yuan, Guowen Xu, Hongwei Li +5
Traffic sign recognition (TSR) systems are crucial for autonomous driving but are vulnerable to backdoor attacks. Existing physical backdoor attacks either lack stealth, provide in…
The Ripple Effect: On Unforeseen Complications of Backdoor Attacks
Rui Zhang, Yun Shen, Hongwei Li +5
Recent research highlights concerns about the trustworthiness of third-party Pre-Trained Language Models (PTLMs) due to potential backdoor attacks. These backdoored PTLMs, however,…
BadLingual: A Novel Lingual-Backdoor Attack against Large Language Models
Zihan Wang, Hongwei Li, Rui Zhang +5
In this paper, we present a new form of backdoor attack against Large Language Models (LLMs): lingual-backdoor attacks. The key novelty of lingual-backdoor attacks is that the lang…
MPMA: Preference Manipulation Attack Against Model Context Protocol
Zihan Wang, Rui Zhang, Yu Liu +5
Model Context Protocol (MCP) standardizes interface mapping for large language models (LLMs) to access external data and tools, which revolutionizes the paradigm of tool selection…
DivTrackee versus DynTracker: Promoting Diversity in Anti-Facial Recognition against Dynamic FR Strategy
Wenshu Fan, Minxing Zhang, Hongwei Li +5
The widespread adoption of facial recognition (FR) models raises serious concerns about their potential misuse, motivating the development of anti-facial recognition (AFR) to prote…