Ningfei Wang

Orcid: 0000-0002-4458-7419

According to our database1, Ningfei Wang authored at least 22 papers between 2018 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Links

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Bibliography

2025
Revisiting Physical-World Adversarial Attack on Traffic Sign Recognition: A Commercial Systems Perspective.
Proceedings of the 32nd Annual Network and Distributed System Security Symposium, 2025

2024
ControlLoc: Physical-World Hijacking Attack on Visual Perception in Autonomous Driving.
CoRR, 2024

Towards Robustness Analysis of E-Commerce Ranking System.
CoRR, 2024

Towards Robustness Analysis of E-Commerce Ranking System.
Proceedings of the Companion Proceedings of the ACM on Web Conference 2024, 2024

Intriguing Properties of Diffusion Models: An Empirical Study of the Natural Attack Capability in Text-to-Image Generative Models.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

SlowTrack: Increasing the Latency of Camera-Based Perception in Autonomous Driving Using Adversarial Examples.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Intriguing Properties of Diffusion Models: A Large-Scale Dataset for Evaluating Natural Attack Capability in Text-to-Image Generative Models.
CoRR, 2023

WIP: Towards the Practicality of the Adversarial Attack on Object Tracking in Autonomous Driving.
Proceedings of the Inaugural International Symposium on Vehicle Security and Privacy, 2023

Does Physical Adversarial Example Really Matter to Autonomous Driving? Towards System-Level Effect of Adversarial Object Evasion Attack.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Invited: Waving the Double-Edged Sword: Building Resilient CAVs with Edge and Cloud Computing.
Proceedings of the 60th ACM/IEEE Design Automation Conference, 2023

2022
SoK: On the Semantic AI Security in Autonomous Driving.
CoRR, 2022

Poster: On the System-Level Effectiveness of Physical Object-Hiding Adversarial Attack in Autonomous Driving.
Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security, 2022

2021
Dirty Road Can Attack: Security of Deep Learning based Automated Lane Centering under Physical-World Attack.
Proceedings of the 30th USENIX Security Symposium, 2021

Demo: Security of Deep Learning based Automated Lane Centering under Physical-World Attack.
Proceedings of the IEEE Security and Privacy Workshops, 2021

Demo: Security of Camera-based Perception for Autonomous Driving under Adversarial Attack.
Proceedings of the IEEE Security and Privacy Workshops, 2021

Invisible for both Camera and LiDAR: Security of Multi-Sensor Fusion based Perception in Autonomous Driving Under Physical-World Attacks.
Proceedings of the 42nd IEEE Symposium on Security and Privacy, 2021

2020
Hold Tight and Never Let Go: Security of Deep Learning based Automated Lane Centering under Physical-World Attack.
CoRR, 2020

Security of Deep Learning based Lane Keeping System under Physical-World Adversarial Attack.
CoRR, 2020

Interpretable Deep Learning under Fire.
Proceedings of the 29th USENIX Security Symposium, 2020

2019
Rendered Private: Making GLSL Execution Uniform to Prevent WebGL-based Browser Fingerprinting.
Proceedings of the 28th USENIX Security Symposium, 2019

2018
Interpretable Deep Learning under Fire.
CoRR, 2018

Integration of Static and Dynamic Code Stylometry Analysis for Programmer De-anonymization.
Proceedings of the 11th ACM Workshop on Artificial Intelligence and Security, 2018


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