| Dirty Road Can Attack: Security of Deep Learning based Automated Lane Centering under Physical-World Attack T Sato, J Shen, N Wang, YJ Jia, X Lin, QA Chen Proceedings of the 29th USENIX Security Symposium, 2021, 2021 | 161* | 2021 |
| Sok: On the semantic ai security in autonomous driving J Shen, N Wang, Z Wan, Y Luo, T Sato, Z Hu, X Zhang, S Guo, Z Zhong, ... arXiv preprint arXiv:2203.05314, 2022 | 44 | 2022 |
| Does physical adversarial example really matter to autonomous driving? towards system-level effect of adversarial object evasion attack N Wang, Y Luo, T Sato, K Xu, QA Chen Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 35 | 2023 |
| Semi-supervised Semantics-guided Adversarial Training for Robust Trajectory Prediction R Jiao, X Liu, T Sato, QA Chen, Q Zhu Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 32* | 2023 |
| LiDAR Spoofing Meets the New-Gen: Capability Improvements, Broken Assumptions, and New Attack Strategies T Sato, Y Hayakawa, R Suzuki, Y Shiiki, K Yoshioka, QA Chen arXiv preprint arXiv:2303.10555, 2023 | 20* | 2023 |
| End-to-end uncertainty-based mitigation of adversarial attacks to automated lane centering R Jiao, H Liang, T Sato, J Shen, QA Chen, Q Zhu 2021 IEEE Intelligent Vehicles Symposium (IV), 266-273, 2021 | 20 | 2021 |
| Security of deep learning based lane keeping system under physical-world adversarial attack T Sato, J Shen, N Wang, YJ Jia, X Lin, QA Chen arXiv preprint arXiv:2003.01782, 2020 | 20 | 2020 |
| Towards driving-oriented metric for lane detection models T Sato, QA Chen Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 16 | 2022 |
| Learning representation for anomaly detection of vehicle trajectories R Jiao, J Bai, X Liu, T Sato, X Yuan, QA Chen, Q Zhu 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2023 | 15 | 2023 |
| Invisible Reflections: Leveraging Infrared Laser Reflections to Target Traffic Sign Perception T Sato, SHV Bhupathiraju, M Clifford, T Sugawara, QA Chen, S Rampazzi arXiv preprint arXiv:2401.03582, 2024 | 13 | 2024 |
| Security of camera-based perception for autonomous driving under adversarial attack C DiPalma, N Wang, T Sato, QA Chen 2021 IEEE Security and Privacy Workshops (SPW), 243-243, 2021 | 13 | 2021 |
| WIP: Infrared Laser Reflection Attack Against Traffic Sign Recognition Systems T Sato, SH Bhupathiraju, M Clifford, T Sugawara, QA Chen, S Rampazzi ISOC Symposium on Vehicle Security and Privacy (VehicleSec), 2023 | 12 | 2023 |
| Exploring backdoor attacks against large language model-based decision making R Jiao, S Xie, J Yue, T Sato, L Wang, Y Wang, QA Chen, Q Zhu arXiv preprint arXiv:2405.20774, 2024 | 8 | 2024 |
| Poster: On the system-level effectiveness of physical object-hiding adversarial attack in autonomous driving N Wang, Y Luo, T Sato, K Xu, QA Chen Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications …, 2022 | 8 | 2022 |
| Intriguing Properties of Diffusion Models: An Empirical Study of the Natural Attack Capability in Text-to-Image Generative Models T Sato, J Yue, N Chen, N Wang, QA Chen Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 7* | 2024 |
| Waving the double-edged sword: Building resilient cavs with edge and cloud computing X Liu, Y Luo, A Goeckner, T Chakraborty, R Jiao, N Wang, Y Wang, T Sato, ... 2023 60th ACM/IEEE Design Automation Conference (DAC), 1-4, 2023 | 7 | 2023 |
| Wip: End-to-end analysis of adversarial attacks to automated lane centering systems H Liang, R Jiao, T Sato, J Shen, QA Chen, Q Zhu Workshop on Automotive and Autonomous Vehicle Security (AutoSec'21), 2021 | 7 | 2021 |
| Poster: Towards large-scale measurement study on LiDAR spoofing attacks against object detection T Sato, Y Hayakawa, R Suzuki, Y Shiiki, K Yoshioka, QA Chen Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications …, 2022 | 6 | 2022 |
| On robustness of lane detection models to physical-world adversarial attacks in autonomous driving T Sato, QA Chen arXiv preprint arXiv:2107.02488, 2021 | 6 | 2021 |
| WIP: Deployability improvement, stealthiness user study, and safety impact assessment on real vehicle for dirty road patch attack T Sato, J Shen, N Wang, YJ Jia, X Lin, QA Chen Workshop on Automotive and Autonomous Vehicle Security (AutoSec) 2021, 25, 2021 | 6 | 2021 |
Alfred ChenAssistant Professor, University of California, IrvineΗ διεύθυνση ηλεκτρονικού ταχυδρομείου έχει επαληθευτεί στον τομέα uci.edu