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Publication search results
found 51 matches
- 2024
- Minzhou Pan, Zhenting Wang, Xin Dong, Vikash Sehwag, Lingjuan Lyu, Xue Lin:
Finding needles in a haystack: A Black-Box Approach to Invisible Watermark Detection. CoRR abs/2403.15955 (2024) - Patrick Chao, Edoardo Debenedetti, Alexander Robey, Maksym Andriushchenko, Francesco Croce, Vikash Sehwag, Edgar Dobriban, Nicolas Flammarion, George J. Pappas, Florian Tramèr, Hamed Hassani, Eric Wong:
JailbreakBench: An Open Robustness Benchmark for Jailbreaking Large Language Models. CoRR abs/2404.01318 (2024) - Zhenting Wang, Vikash Sehwag, Chen Chen, Lingjuan Lyu, Dimitris N. Metaxas, Shiqing Ma:
How to Trace Latent Generative Model Generated Images without Artificial Watermark? CoRR abs/2405.13360 (2024) - Xiangyu Qi, Yangsibo Huang, Yi Zeng, Edoardo Debenedetti, Jonas Geiping, Luxi He, Kaixuan Huang, Udari Madhushani, Vikash Sehwag, Weijia Shi, Boyi Wei, Tinghao Xie, Danqi Chen, Pin-Yu Chen, Jeffrey Ding, Ruoxi Jia, Jiaqi Ma, Arvind Narayanan, Weijie J. Su, Mengdi Wang, Chaowei Xiao, Bo Li, Dawn Song, Peter Henderson, Prateek Mittal:
AI Risk Management Should Incorporate Both Safety and Security. CoRR abs/2405.19524 (2024) - Zhenting Wang, Chen Chen, Vikash Sehwag, Minzhou Pan, Lingjuan Lyu:
Evaluating and Mitigating IP Infringement in Visual Generative AI. CoRR abs/2406.04662 (2024) - Jie Ren, Yingqian Cui, Chen Chen, Vikash Sehwag, Yue Xing, Jiliang Tang, Lingjuan Lyu:
EnTruth: Enhancing the Traceability of Unauthorized Dataset Usage in Text-to-image Diffusion Models with Minimal and Robust Alterations. CoRR abs/2406.13933 (2024) - 2023
- Sihui Dai, Saeed Mahloujifar, Chong Xiang, Vikash Sehwag, Pin-Yu Chen, Prateek Mittal:
MultiRobustBench: Benchmarking Robustness Against Multiple Attacks. ICML 2023: 6760-6785 - Tong Wu, Feiran Jia, Xiangyu Qi, Jiachen T. Wang, Vikash Sehwag, Saeed Mahloujifar, Prateek Mittal:
Uncovering Adversarial Risks of Test-Time Adaptation. ICML 2023: 37456-37495 - Xinyu Tang, Ashwinee Panda, Vikash Sehwag, Prateek Mittal:
Differentially Private Image Classification by Learning Priors from Random Processes. NeurIPS 2023 - Edoardo Debenedetti, Vikash Sehwag, Prateek Mittal:
A Light Recipe to Train Robust Vision Transformers. SaTML 2023: 225-253 - Nicholas Carlini, Jamie Hayes, Milad Nasr, Matthew Jagielski, Vikash Sehwag, Florian Tramèr, Borja Balle, Daphne Ippolito, Eric Wallace:
Extracting Training Data from Diffusion Models. USENIX Security Symposium 2023: 5253-5270 - Tong Wu, Feiran Jia, Xiangyu Qi, Jiachen T. Wang, Vikash Sehwag, Saeed Mahloujifar, Prateek Mittal:
Uncovering Adversarial Risks of Test-Time Adaptation. CoRR abs/2301.12576 (2023) - Nicholas Carlini, Jamie Hayes, Milad Nasr, Matthew Jagielski, Vikash Sehwag, Florian Tramèr, Borja Balle, Daphne Ippolito, Eric Wallace:
Extracting Training Data from Diffusion Models. CoRR abs/2301.13188 (2023) - Sihui Dai, Saeed Mahloujifar, Chong Xiang, Vikash Sehwag, Pin-Yu Chen, Prateek Mittal:
MultiRobustBench: Benchmarking Robustness Against Multiple Attacks. CoRR abs/2302.10980 (2023) - Xinyu Tang, Ashwinee Panda, Vikash Sehwag, Prateek Mittal:
Differentially Private Image Classification by Learning Priors from Random Processes. CoRR abs/2306.06076 (2023) - Edoardo Debenedetti, Zishen Wan, Maksym Andriushchenko, Vikash Sehwag, Kshitij Bhardwaj, Bhavya Kailkhura:
Scaling Compute Is Not All You Need for Adversarial Robustness. CoRR abs/2312.13131 (2023) - 2022
- Tong Wu, Tianhao Wang, Vikash Sehwag, Saeed Mahloujifar, Prateek Mittal:
Just Rotate it: Deploying Backdoor Attacks via Rotation Transformation. AISec@CCS 2022: 91-102 - Vikash Sehwag, Caner Hazirbas, Albert Gordo, Firat Ozgenel, Cristian Canton-Ferrer:
Generating High Fidelity Data from Low-density Regions using Diffusion Models. CVPR 2022: 11482-11491 - Vikash Sehwag, Saeed Mahloujifar, Tinashe Handina, Sihui Dai, Chong Xiang, Mung Chiang, Prateek Mittal:
Robust Learning Meets Generative Models: Can Proxy Distributions Improve Adversarial Robustness? ICLR 2022 - Christian Cianfarani, Arjun Nitin Bhagoji, Vikash Sehwag, Ben Y. Zhao, Heather Zheng, Prateek Mittal:
Understanding Robust Learning through the Lens of Representation Similarities. NeurIPS 2022 - Vikash Sehwag, Caner Hazirbas, Albert Gordo, Firat Ozgenel, Cristian Canton-Ferrer:
Generating High Fidelity Data from Low-density Regions using Diffusion Models. CoRR abs/2203.17260 (2022) - Christian Cianfarani, Arjun Nitin Bhagoji, Vikash Sehwag, Ben Y. Zhao, Prateek Mittal:
Understanding Robust Learning through the Lens of Representation Similarities. CoRR abs/2206.09868 (2022) - Tong Wu, Tianhao Wang, Vikash Sehwag, Saeed Mahloujifar, Prateek Mittal:
Just Rotate it: Deploying Backdoor Attacks via Rotation Transformation. CoRR abs/2207.10825 (2022) - Edoardo Debenedetti, Vikash Sehwag, Prateek Mittal:
A Light Recipe to Train Robust Vision Transformers. CoRR abs/2209.07399 (2022) - Ashwinee Panda, Xinyu Tang, Vikash Sehwag, Saeed Mahloujifar, Prateek Mittal:
DP-RAFT: A Differentially Private Recipe for Accelerated Fine-Tuning. CoRR abs/2212.04486 (2022) - 2021
- Prasad Nagabhushanamgari, Vikash Sehwag, Indrajit Chakrabarti, Santanu Chattopadhyay:
Embedding delay-based physical unclonable functions in networks-on-chip. IET Circuits Devices Syst. 15(1): 27-41 (2021) - Hung T. Nguyen, Vikash Sehwag, Seyyedali Hosseinalipour, Christopher G. Brinton, Mung Chiang, H. Vincent Poor:
Fast-Convergent Federated Learning. IEEE J. Sel. Areas Commun. 39(1): 201-218 (2021) - Vikash Sehwag, Mung Chiang, Prateek Mittal:
SSD: A Unified Framework for Self-Supervised Outlier Detection. ICLR 2021 - Arjun Nitin Bhagoji, Daniel Cullina, Vikash Sehwag, Prateek Mittal:
Lower Bounds on Cross-Entropy Loss in the Presence of Test-time Adversaries. ICML 2021: 863-873 - Vikash Sehwag, Jack W. Stokes, Cha Zhang:
Beyond $L_{p}$ Norms: Delving Deeper into Robustness to Physical Image Transformations. MILCOM 2021: 189-196
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