Generating 3d adversarial point clouds C Xiang, CR Qi, B Li Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 338 | 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 | 179* | 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 | 178 | 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 | 85 | 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 | 80 | 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 | 60 | 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 | 53 | 2020 |
PatchGuard++: Efficient Provable Attack Detection against Adversarial Patches C Xiang, P Mittal ICLR Workshop on Security and Safety in Machine Learning Systems, 2021 | 45 | 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 | 19 | 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 | 18 | 2024 |
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 | 12 | 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 | 9 | 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 | 6 | 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 | 3 | 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 33rd USENIX Security Symposium (USENIX Security 24), 3675-3692, 2024 | 2 | 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 | 1 | 2020 |
Instructional Segment Embedding: Improving LLM Safety with Instruction Hierarchy T Wu, S Zhang, K Song, S Xu, S Zhao, R Agrawal, SR Indurthi, C Xiang, ... arXiv preprint arXiv:2410.09102, 2024 | | 2024 |
Position Paper: Beyond Robustness Against Single Attack Types S Dai, C Xiang, T Wu, P Mittal arXiv preprint arXiv:2405.01349, 2024 | | 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 | | |