Chong Xiang
Chong Xiang
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Generating 3d adversarial point clouds
C Xiang, CR Qi, B Li
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019
Robust learning meets generative models: Can proxy distributions improve adversarial robustness?
V Sehwag, S Mahloujifar, T Handina, S Dai, C Xiang, M Chiang, P Mittal
10th International Conference on Learning Representations, 2022
PatchGuard: A Provably Robust Defense against Adversarial Patches via Small Receptive Fields and Masking
C Xiang, AN Bhagoji, V Sehwag, P Mittal
30th {USENIX} Security Symposium ({USENIX} Security 21), 2021
Differentially Private Data Generative Models
Q Chen, C Xiang, M Xue, B Li, N Borisov, D Kaarfar, H Zhu
arXiv preprint arXiv:1812.02274, 2018
{PatchCleanser}: Certifiably Robust Defense against Adversarial Patches for Any Image Classifier
C Xiang, S Mahloujifar, P Mittal
31st USENIX Security Symposium (USENIX Security 22), 2065-2082, 2022
DetectorGuard: Provably Securing Object Detectors against Localized Patch Hiding Attacks
C Xiang, P Mittal
Proceedings of the 2021 ACM SIGSAC Conference on Computer and Communications …, 2021
Voiceprint Mimicry Attack Towards Speaker Verification System in Smart Home
L Zhang, Y Meng, J Yu, C Xiang, B Falk, H Zhu
IEEE INFOCOM 2020-IEEE Conference on Computer Communications, 377-386, 2020
PatchGuard++: Efficient Provable Attack Detection against Adversarial Patches
C Xiang, P Mittal
ICLR Workshop on Security and Safety in Machine Learning Systems, 2021
Objectseeker: Certifiably robust object detection against patch hiding attacks via patch-agnostic masking
C Xiang, A Valtchanov, S Mahloujifar, P Mittal
2023 IEEE Symposium on Security and Privacy (SP), 1329-1347, 2023
APPCLASSIFIER: automated app inference on encrypted traffic via meta data analysis
C Xiang, Q Chen, M Xue, H Zhu
2018 IEEE Global Communications Conference (GLOBECOM), 1-7, 2018
No-jump-into-latency in China's internet! toward last-mile hop count based IP geo-localization
C Xiang, X Wang, Q Chen, M Xue, Z Gao, H Zhu, C Chen, Q Fan
Proceedings of the International Symposium on Quality of Service, 1-10, 2019
MultiRobustBench: Benchmarking Robustness Against Multiple Attacks
S Dai, S Mahloujifar, C Xiang, V Sehwag, PY Chen, P Mittal
International Conference on Machine Learning, 2023
PatchCURE: Improving Certifiable Robustness, Model Utility, and Computation Efficiency of Adversarial Patch Defenses
C Xiang, T Wu, S Dai, J Petit, S Jana, P Mittal
arXiv preprint arXiv:2310.13076, 2023
Short: Certifiably Robust Perception Against Adversarial Patch Attacks: A Survey
C Xiang, C Sitawarin, T Wu, P Mittal
Inaugural Symposium on Vehicle Security and Privacy, 2023
Certifiably Robust RAG against Retrieval Corruption
C Xiang, T Wu, Z Zhong, D Wagner, D Chen, P Mittal
arXiv preprint arXiv:2405.15556, 2024
Robustness from perception
S Mahloujifar, C Xiang, V Sehwag, S Dai, P Mittal
ICLR Workshop on Security and Safety in Machine Learning Systems, 2020
Position Paper: Beyond Robustness Against Single Attack Types
S Dai, C Xiang, T Wu, P Mittal
arXiv preprint arXiv:2405.01349, 2024
WIP: Towards a Certifiably Robust Defense for Multi-label Classifiers Against Adversarial Patches
DG Jacob, C Xiang, P Mittal
Generating 3D Adversarial Point Clouds Supplementary Material
C Xiang, CR Qi, B Li
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