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Takami Sato
Takami Sato
Dirección de correo verificada de uci.edu - Página principal
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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
121*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
272022
Semi-supervised semantics-guided adversarial training for trajectory prediction
R Jiao, X Liu, T Sato, QA Chen, Q Zhu
arXiv preprint arXiv:2205.14230, 2022
18*2022
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
162021
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
152020
Towards driving-oriented metric for lane detection models
T Sato, QA Chen
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022
102022
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
92023
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
92023
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
92021
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
ISOC Network and Distributed System Security Symposium (NDSS), 2024
62024
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
62023
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
62023
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
62022
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
62021
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
62021
On robustness of lane detection models to physical-world adversarial attacks in autonomous driving
T Sato, QA Chen
arXiv preprint arXiv:2107.02488, 2021
42021
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
32024
Revisiting LiDAR Spoofing Attack Capabilities against Object Detection: Improvements, Measurement, and New Attack
T Sato, Y Hayakawa, R Suzuki, Y Shiiki, K Yoshioka, QA Chen
arXiv preprint arXiv:2303.10555, 2023
32023
WIP: Practical removal attacks on LiDAR-based object detection in autonomous driving
T Sato, Y Hayakawa, R Suzuki, Y Shiiki, K Yoshioka, QA Chen
ISOC Symposium on Vehicle Security and Privacy (VehicleSec), 2023
32023
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
32022
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