no code implementations • 15 Sep 2024 • Ningfei Wang, Shaoyuan Xie, Takami Sato, Yunpeng Luo, Kaidi Xu, Qi Alfred Chen
We design new attack success metrics that can mathematically model the impacts of such design on the TSR system-level attack success, and use them to revisit existing attacks.
no code implementations • 9 Jun 2024 • Chen Ma, Ningfei Wang, Zhengyu Zhao, Qian Wang, Qi Alfred Chen, Chao Shen
Extensive evaluations demonstrate the superior performance of ControlLoc, achieving an impressive average attack success rate of around 98. 1% across various AD visual perceptions and datasets, which is four times greater effectiveness than the existing hijacking attack.
no code implementations • 9 Jun 2024 • Chen Ma, Ningfei Wang, Zhengyu Zhao, Qi Alfred Chen, Chao Shen
Additionally, we conduct AD system-level impact assessments, such as vehicle collisions, using industry-grade AD systems with production-grade AD simulators with a 97% average rate.
no code implementations • 7 Mar 2024 • Ningfei Wang, Yupin Huang, Han Cheng, Jiri Gesi, Xiaojie Wang, Vivek Mittal
As e-commerce retailers use various techniques to improve the quality of search results, we hope that this research offers valuable guidance for measuring the robustness of the ranking systems.
no code implementations • 15 Dec 2023 • Chen Ma, Ningfei Wang, Qi Alfred Chen, Chao Shen
Our evaluation results show that the system-level effects can be significantly improved, i. e., the vehicle crash rate of SlowTrack is around 95% on average while existing works only have around 30%.
no code implementations • CVPR 2024 • Takami Sato, Justin Yue, Nanze Chen, Ningfei Wang, Qi Alfred Chen
The NDD attack shows a significantly high capability to generate low-cost, model-agnostic, and transferable adversarial attacks by exploiting the natural attack capability in diffusion models.
no code implementations • ICCV 2023 • Ningfei Wang, Yunpeng Luo, Takami Sato, Kaidi Xu, Qi Alfred Chen
In this work, we conduct the first measurement study on whether and how effectively the existing designs can lead to system-level effects, especially for the STOP sign-evasion attacks due to their popularity and severity.
no code implementations • 10 Mar 2022 • Junjie Shen, Ningfei Wang, Ziwen Wan, Yunpeng Luo, Takami Sato, Zhisheng Hu, Xinyang Zhang, Shengjian Guo, Zhenyu Zhong, Kang Li, Ziming Zhao, Chunming Qiao, Qi Alfred Chen
In this paper, we perform the first systematization of knowledge of such growing semantic AD AI security research space.
no code implementations • 14 Sep 2020 • Takami Sato, Junjie Shen, Ningfei Wang, Yunhan Jack Jia, Xue Lin, Qi Alfred Chen
Automated Lane Centering (ALC) systems are convenient and widely deployed today, but also highly security and safety critical.
no code implementations • 3 Mar 2020 • Takami Sato, Junjie Shen, Ningfei Wang, Yunhan Jack Jia, Xue Lin, Qi Alfred Chen
Lane-Keeping Assistance System (LKAS) is convenient and widely available today, but also extremely security and safety critical.
no code implementations • 3 Dec 2018 • Xinyang Zhang, Ningfei Wang, Hua Shen, Shouling Ji, Xiapu Luo, Ting Wang
The improved interpretability is believed to offer a sense of security by involving human in the decision-making process.