Takami Sato

发表

WIP: Deployability Improvement, Stealthiness User Study, and Safety Impact Assessment on Real Vehicle for Dirty Road Patch Attack

Qi Alfred Chen, Yunhan Jia, Ningfei Wang, 2021 .

Video Signature Robust to Modifications for Large-scale Video Identification

Takami Sato, K. Iwamoto, R. Oami, 2013 .

WIP: On Robustness of Lane Detection Models to Physical-World Adversarial Attacks

Qi Alfred Chen, Takami Sato, 2022 .

Dirty Road Can Attack: Security of Deep Learning based Automated Lane Centering under Physical-World Attack

Qi Alfred Chen, Yunhan Jia, Ningfei Wang, 2020, USENIX Security Symposium.

Demo: Remote Adversarial Attack on Automated Lane Centering*

Qi Alfred Chen, Yulong Cao, Takami Sato, 2022 .

WIP: End-to-End Analysis of Adversarial Attacks to Automated Lane Centering Systems

Qi Alfred Chen, Junjie Shen, Takami Sato, 2021 .

Poster: Towards Large-Scale Measurement Study on LiDAR Spoofing Attacks against Object Detection

Qi Alfred Chen, Takami Sato, Yukihiko Hayakawa, 2022, CCS.

Towards Driving-Oriented Metric for Lane Detection Models

Qi Alfred Chen, Takami Sato, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Revisiting LiDAR Spoofing Attack Capabilities against Object Detection: Improvements, Measurement, and New Attack

Qi Alfred Chen, Takami Sato, Y. Shiiki, 2023, ArXiv.

SoK: On the Semantic AI Security in Autonomous Driving

Qi Alfred Chen, Yunpeng Luo, Ningfei Wang, 2022, ArXiv.

Hold Tight and Never Let Go: Security of Deep Learning based Automated Lane Centering under Physical-World Attack pdf

Ningfei Wang, Junjie Shen, Qi Alfred Chen, 2020, ArXiv.

Security of Deep Learning based Lane Keeping System under Physical-World Adversarial Attack pdf

Ningfei Wang, Junjie Shen, Qi Alfred Chen, 2020, ArXiv.

Semi-supervised Semantics-guided Adversarial Training for Robust Trajectory Prediction

Qi Alfred Chen, Takami Sato, Qi Zhu, 2022, 2023 IEEE/CVF International Conference on Computer Vision (ICCV).

On Robustness of Lane Detection Models to Physical-World Adversarial Attacks in Autonomous Driving pdf

Qi Alfred Chen, Takami Sato, Takami Sato, 2021, ArXiv.

Intriguing Properties of Diffusion Models: A Large-Scale Dataset for Evaluating Natural Attack Capability in Text-to-Image Generative Models

Qi Alfred Chen, Ningfei Wang, Takami Sato, 2023, ArXiv.

Does Physical Adversarial Example Really Matter to Autonomous Driving? Towards System-Level Effect of Adversarial Object Evasion Attack

Qi Alfred Chen, Ningfei Wang, Takami Sato, 2023, ArXiv.

Poster: On the System-Level Effectiveness of Physical Object-Hiding Adversarial Attack in Autonomous Driving

Qi Alfred Chen, Ningfei Wang, Takami Sato, 2022, Conference on Computer and Communications Security.

Demo: Security of Camera-based Perception for Autonomous Driving under Adversarial Attack

Qi Alfred Chen, Takami Sato, Ningfei Wang, 2021, 2021 IEEE Security and Privacy Workshops (SPW).

WIP: Practical Removal Attacks on LiDAR-based Object Detection in Autonomous Driving

Qi Alfred Chen, Takami Sato, Y. Shiiki, 2023, Proceedings Inaugural International Symposium on Vehicle Security & Privacy.

WIP: Infrared Laser Reflection Attack Against Traffic Sign Recognition Systems

Qi Alfred Chen, Takami Sato, Sara Rampazzi, 2023, Proceedings Inaugural International Symposium on Vehicle Security & Privacy.

Learning Representation for Anomaly Detection of Vehicle Trajectories

Qi Alfred Chen, Takami Sato, Ruochen Jiao, 2023, ArXiv.

Security of Deep Learning based Lane Keeping System under Physical-World Adversarial Attack

Qi Alfred Chen, Yunhan Jia, X. Lin, 2020, ArXiv.

End-to-end Uncertainty-based Mitigation of Adversarial Attacks to Automated Lane Centering

Qi Zhu, Junjie Shen, Qi Alfred Chen, 2021, 2021 IEEE Intelligent Vehicles Symposium (IV).

WIP: Towards Practical LiDAR Spoofing Attack against Vehicles Driving at Cruising Speeds

Takami Sato, Ryo Suzuki, Kentaro Yoshioka, 2022 .

Exploring Backdoor Attacks against Large Language Model-based Decision Making

Takami Sato, Lixu Wang, Ruochen Jiao, 2024, 2405.20774.

Demo: Security of Deep Learning based Automated Lane Centering under Physical-World Attack

Ningfei Wang, Junjie Shen, Qi Alfred Chen, 2021, 2021 IEEE Security and Privacy Workshops (SPW).

Dirty Road Can Attack: Security of Deep Learning based Automated Lane Centering under Physical-World Attack

Junjie Shen, Qi Alfred Chen, Takami Sato, 2020, USENIX Security Symposium.