Backdoor attack in autonomous vehicles

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Yang, Shuhan CC F23.pdf (1.32 MB)

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Date
2023-12
Authors
Yang, Shuhan
Major Professor
Wongpiromsarn, Tichakorn
Advisor
Committee Member
Aduri, Pavan
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Abstract
In recent years, autonomous vehicles have drawn significant attention, especially those based on LiDAR object detection systems. These systems are well-known for their high accuracy in sensing the environment and hence play an important role in the performance of various autonomous vehicles. For example, autonomous vehicles like Waymo from Google and Nuro, equipped with LiDAR systems for navigation and safety, have already been applied to public roads. However, despite the high efficiency of LiDAR object detection systems in perceiving the surrounding environment, this risk of these systems being susceptible to potential attacks cannot be overlooked. This project aims to explore backdoor attacks toward the LiDAR object detection problem.
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CC0 1.0 Universal, 2023