Toward Robust 3D Perception for Autonomous Vehicles: A Review of Adversarial Attacks and Countermeasures
Article
Article Title | Toward Robust 3D Perception for Autonomous Vehicles: A Review of Adversarial Attacks and Countermeasures |
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ERA Journal ID | 3746 |
Article Category | Article |
Authors | Yasas, K. T., Perera, Asanka G., Anavatti, Sreenatha and Garratt, Matt |
Journal Title | IEEE Transactions on Intelligent Transportation Systems |
Number of Pages | 27 |
Year | 2024 |
Publisher | IEEE (Institute of Electrical and Electronics Engineers) |
Place of Publication | United States |
ISSN | 1524-9050 |
1558-0016 | |
Digital Object Identifier (DOI) | https://doi.org/10.1109/TITS.2024.3456293 |
Web Address (URL) | https://ieeexplore.ieee.org/abstract/document/10682109 |
Abstract | At present the perception system of autonomous vehicles is grounded on 3D vision technologies along with deep learning to process depth information. Although deep learning models for 3D perception give promising results, recent research demonstrates that they are also vulnerable to adversarial attacks similar to deep learning models trained on 2D images. As a result, it is essential to further explore the vulnerabilities of 3D perception models in autonomous vehicles and find methods to cope with the risks associated with these adversarial vulnerabilities, in order to improve the social acceptance of commercial autonomous vehicles. This study aims to provide an in-depth overview of the recent adversarial attacks and countermeasures against 3D perception models on autonomous vehicles. Further, challenges associated with the research domain and future research directions are highlighted to make autonomous vehicles robust against adversarial attacks. |
Keywords | Adversarial attack; autonomous vehicles; 3D perception; deep learning; LiDAR |
Contains Sensitive Content | Does not contain sensitive content |
ANZSRC Field of Research 2020 | 4007. Control engineering, mechatronics and robotics |
Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
Byline Affiliations | University of New South Wales |
School of Engineering |
https://research.usq.edu.au/item/z98y0/toward-robust-3d-perception-for-autonomous-vehicles-a-review-of-adversarial-attacks-and-countermeasures
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