468 citations · 922 across the 20 of their papers we have counts for
7 papers · 1 filter
On Adversarial Robustness of 3D Point Cloud Classification under Adaptive Attacks
Jiachen Sun, Karl Koenig, Yulong Cao +2
3D point clouds play pivotal roles in various safety-critical applications, such as autonomous driving, which desires the underlying deep neural networks to be robust to adversaria…
Impact Evaluation of Falsified Data Attacks on Connected Vehicle Based Traffic Signal Control
Shihong Ed Huang, Wai Wong, Yiheng Feng +3
Connected vehicle (CV) technology enables data exchange between vehicles and transportation infrastructure and therefore has great potentials to improve current traffic signal cont…
Dirty Road Can Attack: Security of Deep Learning based Automated Lane Centering under Physical-World Attack
Takami Sato, Junjie Shen, Ningfei Wang +3
Automated Lane Centering (ALC) systems are convenient and widely deployed today, but also highly security and safety critical. In this work, we are the first to systematically stud…
Towards Robust LiDAR-based Perception in Autonomous Driving: General Black-box Adversarial Sensor Attack and Countermeasures
Jiachen Sun, Yulong Cao, Qi Alfred Chen +1
Perception plays a pivotal role in autonomous driving systems, which utilizes onboard sensors like cameras and LiDARs (Light Detection and Ranging) to assess surroundings. Recent s…
Drift with Devil: Security of Multi-Sensor Fusion based Localization in High-Level Autonomous Driving under GPS Spoofing (Extended Version)
Junjie Shen, Jun Yeon Won, Zeyuan Chen +1
For high-level Autonomous Vehicles (AV), localization is highly security and safety critical. One direct threat to it is GPS spoofing, but fortunately, AV systems today predominant…
Threat Detection and Investigation with System-level Provenance Graphs: A Survey
Zhenyuan Li, Qi Alfred Chen, Runqing Yang +1
With the development of information technology, the border of the cyberspace gets much broader, exposing more and more vulnerabilities to attackers. Traditional mitigation-based de…
Security of Deep Learning based Lane Keeping System under Physical-World Adversarial Attack
Takami Sato, Junjie Shen, Ningfei Wang +3
Lane-Keeping Assistance System (LKAS) is convenient and widely available today, but also extremely security and safety critical. In this work, we design and implement the first sys…