دورية أكاديمية

Cam-PC: A Novel Method for Camouflaging Point Clouds to Counter Adversarial Deception in Remote Sensing

التفاصيل البيبلوغرافية
العنوان: Cam-PC: A Novel Method for Camouflaging Point Clouds to Counter Adversarial Deception in Remote Sensing
المؤلفون: Bo Wei, Teng Huang, Xi Zhang, Jiaming Liang, Yunhao Li, Cong Cao, Dan Li, Yongfeng Chen, Huagang Xiong, Feng Jiang, Xiqiu Zhang
المصدر: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 56-67 (2024)
بيانات النشر: IEEE, 2024.
سنة النشر: 2024
المجموعة: LCC:Ocean engineering
LCC:Geophysics. Cosmic physics
مصطلحات موضوعية: Adversarial attack, physical simulation, point cloud, remote sensing image, Ocean engineering, TC1501-1800, Geophysics. Cosmic physics, QC801-809
الوصف: Synthetic aperture LiDAR can generate point cloud data, which is widely used in 3-D scene reconstruction. However, existing point cloud object recognition methods are vulnerable to adversarial attacks, and such attacks are difficult to transfer to the physical world. Even if adversarial perturbations are added to physical objects, they are easily detectable by other sensors. Our proposed method includes two modules, R-D and D-R, which generate more concealed adversarial point cloud samples by modifying digital and physical features. The R-D module maps real-world entities to point cloud data in the digital world and generates adversarial samples by modifying signal amplitude values. The D-R module constructs adversarial objects by modifying the surface diffuse reflectance of the target object based on ray tracing and correspondences between digital and physical features. Our method is evaluated through experiments on attack effectiveness, robustness after subsampling and transferability, demonstrating its effectiveness, and achieving new state-of-the-art performance.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2151-1535
العلاقة: https://ieeexplore.ieee.org/document/10285331Test/; https://doaj.org/toc/2151-1535Test
DOI: 10.1109/JSTARS.2023.3324483
الوصول الحر: https://doaj.org/article/1b8a0f54cf7a414fb4977cef157f48ddTest
رقم الانضمام: edsdoj.1b8a0f54cf7a414fb4977cef157f48dd
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:21511535
DOI:10.1109/JSTARS.2023.3324483