58 citations · 66 across the 7 of their papers we have counts for
9 papers
Speculative Safety Honeypot: Toward Proactive Defense Against Multi-turn Agent Attacks
Zezhong Wang, Xueyang Tang, Rui Lian +2
As Large Language Model (LLM) agents are increasingly deployed in complex environments, multi-turn interaction attacks have become a significant security challenge. Existing detect…
TwinIR: Coordinated Invisible Dual-Point Attacks on Online HD Map Construction
Haibo Hu, Jianghuai Deng, Chen Tang +3
Online HD map construction is critical to prediction and planning in autonomous driving. We find that existing physical attacks against online map construction are limited by a cro…
OmniSCS: Omni Safety-Critical Scenario Synthesis for Autonomous Driving via a Fully Editable Driving World
Xiaoyun Dong, Qian Xu, Yang Lu +3
The synthesis of safety-critical scenarios (SCS) and their evaluation through closed-loop simulations are crucial for developing robust autonomous driving systems. A key aspect of…
SATMapTR: Satellite Image Enhanced Online HD Map Construction
Bingyuan Huang, Guanyi Zhao, Qian Xu +3
High-definition (HD) maps are evolving from pre-annotated to real-time construction to better support autonomous driving in diverse scenarios. However, this process is hindered by…
Asymmetry Vulnerability and Physical Attacks on Online Map Construction for Autonomous Driving
Yang Lou, Haibo Hu, Qun Song +5
High-definition maps provide precise environmental information essential for prediction and planning in autonomous driving systems. Due to the high cost of labeling and maintenance…
VLM-C4L: Continual Core Dataset Learning with Corner Case Optimization via Vision-Language Models for Autonomous Driving
Haibo Hu, Jiacheng Zuo, Yang Lou +6
With the widespread adoption and deployment of autonomous driving, handling complex environments has become an unavoidable challenge. Due to the scarcity and diversity of extreme s…
A First Physical-World Trajectory Prediction Attack via LiDAR-induced Deceptions in Autonomous Driving
Yang Lou, Yi Zhu, Qun Song +4
Trajectory prediction forecasts nearby agents' moves based on their historical trajectories. Accurate trajectory prediction is crucial for autonomous vehicles. Existing attacks com…
Uncertainty-Encoded Multi-Modal Fusion for Robust Object Detection in Autonomous Driving
Yang Lou, Qun Song, Qian Xu +2
Multi-modal fusion has shown initial promising results for object detection of autonomous driving perception. However, many existing fusion schemes do not consider the quality of e…
Evaluating Adversarial Attacks on Driving Safety in Vision-Based Autonomous Vehicles
Jindi Zhang, Yang Lou, Jianping Wang +3
In recent years, many deep learning models have been adopted in autonomous driving. At the same time, these models introduce new vulnerabilities that may compromise the safety of a…