research-article

PointCRT: Detecting Backdoor in 3D Point Cloud via Corruption Robustness

Authors:

Junhui HouAuthors Info & Claims

MM '23: Proceedings of the 31st ACM International Conference on Multimedia

Pages 666 - 675

https://doi.org/10.1145/3581783.3612456

Published: 27 October 2023 Publication History

Abstract

Backdoor attacks for point clouds have elicited mounting interest with the proliferation of deep learning. The point cloud classifiers can be vulnerable to malicious actors who seek to manipulate or fool the model with specific backdoor triggers. Detecting and rejecting backdoor samples during the inference stage can effectively alleviate backdoor attacks. Recently, some black-box test-time backdoor sample detection methods have been proposed in the 2D image domain, without any underlying assumptions about the backdoor triggers. However, upon examination, we have found that these detection techniques are not effective for 3D point clouds. As a result, there is a pressing need to bridge the gap for the development of a universal approach that is specifically designed for 3D point clouds.

In this paper, we propose the first test-time backdoor sample detection method in 3D point cloud without assumption to the backdoor triggers, called Point Clouds Corruption Robustness Test (PointCRT). Based on the fact that the corruption robustness of clean samples remains relatively stable across various backdoor models, we propose the corruption robustness score to map the features into high-dimensional space. The corruption robustness score is a vector evaluated by label consistency, whose element is the minimum severity level of corruption that changes the label prediction of the victim model. Then, the trigger is identified by detecting the abnormal corruption robustness score through a nonlinear classification. The comprehensive experiments demonstrate PointCRT deals with all cases with the average AUC over 0.934 and F1 score over 0.864, with the enhancement of 18%-28% on ModelNet40. Our codes are available at: https://github.com/CGCL-codes/PointCRT.

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Zhang HHu SWang YZhang LZhou ZWang XZhang YChen CLarson K(2024)Detector collapseProceedings of the Thirty-Third International Joint Conference on Artificial Intelligence10.24963/ijcai.2024/185(1670-1678)Online publication date: 3-Aug-2024
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He PJiao LLi LLiu XLiu FMa WYang SShang RCai JKankanhalli MPrabhakaran BBoll SSubramanian RZheng LSingh VCesar PXie LXu D(2024)Domain Generalization-Aware Uncertainty Introspective Learning for 3D Point Clouds SegmentationProceedings of the 32nd ACM International Conference on Multimedia10.1145/3664647.3681574(651-660)Online publication date: 28-Oct-2024
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Index Terms

PointCRT: Detecting Backdoor in 3D Point Cloud via Corruption Robustness
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
  2. Machine learning

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cover image ACM Conferences

MM '23: Proceedings of the 31st ACM International Conference on Multimedia

October 2023

9913 pages

ISBN:9798400701085

DOI:10.1145/3581783

General Chairs:
Abdulmotaleb El Saddik
University of Ottawa, Canada & MBZUAI, UAE
,
Tao Mei
HiDream.ai, China
,
Rita Cucchiara
University of Modena and Reggio Emilia, Italy
,
Program Chairs:
Marco Bertini
University of Florence, Italy
,
Diana Patricia Tobon Vallejo
Unversidad de Medellin, Colombia
,
Pradeep K. Atrey
University at Albany, State University of New York, USA
,
M. Shamim Hossain
M. Shamim Hossain (King Saud University, KSA

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Published: 27 October 2023

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National Natural Science Foundation of China
National Natural Science Foundation of China
Hubei Province Key R&D Technology Special Innovation Project

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MM '23: The 31st ACM International Conference on Multimedia

October 29 - November 3, 2023

Ottawa ON, Canada

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Cited By

Li MWan WNing YHu SXue LZhang LWang YLarson K(2024)DarkFedProceedings of the Thirty-Third International Joint Conference on Artificial Intelligence10.24963/ijcai.2024/491(4443-4451)Online publication date: 3-Aug-2024
https://dl.acm.org/doi/10.24963/ijcai.2024/491
Zhang HHu SWang YZhang LZhou ZWang XZhang YChen CLarson K(2024)Detector collapseProceedings of the Thirty-Third International Joint Conference on Artificial Intelligence10.24963/ijcai.2024/185(1670-1678)Online publication date: 3-Aug-2024
https://dl.acm.org/doi/10.24963/ijcai.2024/185
He PJiao LLi LLiu XLiu FMa WYang SShang RCai JKankanhalli MPrabhakaran BBoll SSubramanian RZheng LSingh VCesar PXie LXu D(2024)Domain Generalization-Aware Uncertainty Introspective Learning for 3D Point Clouds SegmentationProceedings of the 32nd ACM International Conference on Multimedia10.1145/3664647.3681574(651-660)Online publication date: 28-Oct-2024
https://dl.acm.org/doi/10.1145/3664647.3681574
Liu RLiu ZZhang HZhang GZhang JSunbo Sheng WLiu XJin YCai JKankanhalli MPrabhakaran BBoll SSubramanian RZheng LSingh VCesar PXie LXu D(2024)ColVO: Colonoscopic Visual Odometry Considering Geometric and Photometric ConsistencyProceedings of the 32nd ACM International Conference on Multimedia10.1145/3664647.3681286(8100-8109)Online publication date: 28-Oct-2024
https://dl.acm.org/doi/10.1145/3664647.3681286
Bian YTian SLiu X(2024)iBA: Backdoor Attack on 3D Point Cloud via Reconstructing ItselfIEEE Transactions on Information Forensics and Security10.1109/TIFS.2024.345263019(7994-8008)Online publication date: 30-Aug-2024
https://dl.acm.org/doi/10.1109/TIFS.2024.3452630
Mo XZhang YZhang LLuo WSun NHu SGao SXiang Y(2024)Robust Backdoor Detection for Deep Learning via Topological Evolution Dynamics2024 IEEE Symposium on Security and Privacy (SP)10.1109/SP54263.2024.00174(2048-2066)Online publication date: 19-May-2024
https://doi.org/10.1109/SP54263.2024.00174
Wang XHu SZhang YZhou ZZhang LXu PWan WJin H(2024)ECLIPSE: Expunging Clean-Label Indiscriminate Poisons via Sparse Diffusion PurificationComputer Security – ESORICS 202410.1007/978-3-031-70879-4_8(146-166)Online publication date: 16-Sep-2024
https://dl.acm.org/doi/10.1007/978-3-031-70879-4_8
Wang XLi MXu PLiu WZhang LHu SZhang Y(2024)PointAPA: Towards Availability Poisoning Attacks in 3D Point CloudsComputer Security – ESORICS 202410.1007/978-3-031-70879-4_7(125-145)Online publication date: 16-Sep-2024
https://dl.acm.org/doi/10.1007/978-3-031-70879-4_7

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