Vikash Sehwag

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 52

Top Topics

Diffusion Models

Watermark Detection

Differentially Private

Top Venues

Publications

Vikash Sehwag, Xianghao Kong, Jingtao Li, Michael Spranger, Lingjuan Lyu
Stretching Each Dollar: Diffusion Training from Scratch on a Micro-Budget. CoRR (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 (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 (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 (2024)
Zhenting Wang, Chen Chen, Vikash Sehwag, Minzhou Pan, Lingjuan Lyu
Evaluating and Mitigating IP Infringement in Visual Generative AI. CoRR (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 (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 (2024)
Edoardo Debenedetti, Vikash Sehwag, Prateek Mittal
A Light Recipe to Train Robust Vision Transformers. SaTML (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. USENIX Security Symposium (2023)
Sihui Dai, Saeed Mahloujifar, Chong Xiang, Vikash Sehwag, Pin-Yu Chen, Prateek Mittal
MultiRobustBench: Benchmarking Robustness Against Multiple Attacks. ICML (2023)
Tong Wu, Feiran Jia, Xiangyu Qi, Jiachen T. Wang, Vikash Sehwag, Saeed Mahloujifar, Prateek Mittal
Uncovering Adversarial Risks of Test-Time Adaptation. CoRR (2023)
Xinyu Tang, Ashwinee Panda, Vikash Sehwag, Prateek Mittal
Differentially Private Image Classification by Learning Priors from Random Processes. CoRR (2023)
Xinyu Tang, Ashwinee Panda, Vikash Sehwag, Prateek Mittal
Differentially Private Image Classification by Learning Priors from Random Processes. NeurIPS (2023)
Edoardo Debenedetti, Zishen Wan, Maksym Andriushchenko, Vikash Sehwag, Kshitij Bhardwaj, Bhavya Kailkhura
Scaling Compute Is Not All You Need for Adversarial Robustness. CoRR (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 (2023)
Tong Wu, Feiran Jia, Xiangyu Qi, Jiachen T. Wang, Vikash Sehwag, Saeed Mahloujifar, Prateek Mittal
Uncovering Adversarial Risks of Test-Time Adaptation. ICML (2023)
Sihui Dai, Saeed Mahloujifar, Chong Xiang, Vikash Sehwag, Pin-Yu Chen, Prateek Mittal
MultiRobustBench: Benchmarking Robustness Against Multiple Attacks. CoRR (2023)
Edoardo Debenedetti, Vikash Sehwag, Prateek Mittal
A Light Recipe to Train Robust Vision Transformers. CoRR (2022)
Christian Cianfarani, Arjun Nitin Bhagoji, Vikash Sehwag, Ben Y. Zhao, Prateek Mittal
Understanding Robust Learning through the Lens of Representation Similarities. CoRR (2022)
Tong Wu, Tianhao Wang, Vikash Sehwag, Saeed Mahloujifar, Prateek Mittal
Just Rotate it: Deploying Backdoor Attacks via Rotation Transformation. CoRR (2022)
Tong Wu, Tianhao Wang, Vikash Sehwag, Saeed Mahloujifar, Prateek Mittal
Just Rotate it: Deploying Backdoor Attacks via Rotation Transformation. AISec@CCS (2022)
Vikash Sehwag, Caner Hazirbas, Albert Gordo, Firat Ozgenel, Cristian Canton-Ferrer
Generating High Fidelity Data from Low-density Regions using Diffusion Models. CVPR (2022)
Ashwinee Panda, Xinyu Tang, Vikash Sehwag, Saeed Mahloujifar, Prateek Mittal
DP-RAFT: A Differentially Private Recipe for Accelerated Fine-Tuning. CoRR (2022)
Vikash Sehwag, Caner Hazirbas, Albert Gordo, Firat Ozgenel, Cristian Canton-Ferrer
Generating High Fidelity Data from Low-density Regions using Diffusion Models. CoRR (2022)
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, Mung Chiang, Prateek Mittal
SSD: A Unified Framework for Self-Supervised Outlier Detection. ICLR (2021)
Chong Xiang, Arjun Nitin Bhagoji, Vikash Sehwag, Prateek Mittal
PatchGuard: A Provably Robust Defense against Adversarial Patches via Small Receptive Fields and Masking. USENIX Security Symposium (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)
Francesco Croce, Maksym Andriushchenko, Vikash Sehwag, Edoardo Debenedetti, Nicolas Flammarion, Mung Chiang, Prateek Mittal, Matthias Hein
RobustBench: a standardized adversarial robustness benchmark. NeurIPS Datasets and Benchmarks (2021)
Vikash Sehwag, Saeed Mahloujifar, Tinashe Handina, Sihui Dai, Chong Xiang, Mung Chiang, Prateek Mittal
Improving Adversarial Robustness Using Proxy Distributions. CoRR (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) (2021)
Vikash Sehwag, Jack W. Stokes, Cha Zhang
Beyond $L_{p}$ Norms: Delving Deeper into Robustness to Physical Image Transformations. MILCOM (2021)
Arjun Nitin Bhagoji, Daniel Cullina, Vikash Sehwag, Prateek Mittal
Lower Bounds on Cross-Entropy Loss in the Presence of Test-time Adversaries. CoRR (2021)
Vikash Sehwag, Mung Chiang, Prateek Mittal
SSD: A Unified Framework for Self-Supervised Outlier Detection. CoRR (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) (2021)
Liwei Song, Vikash Sehwag, Arjun Nitin Bhagoji, Prateek Mittal
A Critical Evaluation of Open-World Machine Learning. CoRR (2020)
Vikash Sehwag, Rajvardhan Oak, Mung Chiang, Prateek Mittal
Time for a Background Check! Uncovering the impact of Background Features on Deep Neural Networks. CoRR (2020)
Vikash Sehwag, Shiqi Wang, Prateek Mittal, Suman Jana
On Pruning Adversarially Robust Neural Networks. CoRR (2020)
Hung T. Nguyen, Vikash Sehwag, Seyyedali Hosseinalipour, Christopher G. Brinton, Mung Chiang, H. Vincent Poor
Fast-Convergent Federated Learning. CoRR (2020)
Chong Xiang, Arjun Nitin Bhagoji, Vikash Sehwag, Prateek Mittal
PatchGuard: Provable Defense against Adversarial Patches Using Masks on Small Receptive Fields. CoRR (2020)
Vikash Sehwag, Shiqi Wang, Prateek Mittal, Suman Jana
HYDRA: Pruning Adversarially Robust Neural Networks. NeurIPS (2020)
Francesco Croce, Maksym Andriushchenko, Vikash Sehwag, Nicolas Flammarion, Mung Chiang, Prateek Mittal, Matthias Hein
RobustBench: a standardized adversarial robustness benchmark. CoRR (2020)
Vikash Sehwag, Arjun Nitin Bhagoji, Liwei Song, Chawin Sitawarin, Daniel Cullina, Mung Chiang, Prateek Mittal
Analyzing the Robustness of Open-World Machine Learning. AISec@CCS (2019)
Vikash Sehwag, Arjun Nitin Bhagoji, Liwei Song, Chawin Sitawarin, Daniel Cullina, Mung Chiang, Prateek Mittal
Better the Devil you Know: An Analysis of Evasion Attacks using Out-of-Distribution Adversarial Examples. CoRR (2019)
Vikash Sehwag, Shiqi Wang, Prateek Mittal, Suman Jana
Towards Compact and Robust Deep Neural Networks. CoRR (2019)
Vikash Sehwag, N. Prasad, Indrajit Chakrabarti
A Parallel Stochastic Number Generator With Bit Permutation Networks. IEEE Trans. Circuits Syst. II Express Briefs (2) (2018)
Vikash Sehwag, Chawin Sitawarin, Arjun Nitin Bhagoji, Arsalan Mosenia, Mung Chiang, Prateek Mittal
Not All Pixels are Born Equal: An Analysis of Evasion Attacks under Locality Constraints. CCS (2018)
Vikash Sehwag, Saurav Maji, Mrigank Sharad
Variation Aware Performance Analysis of TFETs for Low-Voltage Computing. iNIS (2016)
Vikash Sehwag, Tanujay Saha
TV-PUF: A Fast Lightweight Analog Physical Unclonable Function. iNIS (2016)
Tanujay Saha, Vikash Sehwag
TV-PUF : A Fast Lightweight Aging-Resistant Threshold Voltage PUF. IACR Cryptol. ePrint Arch. 2016 (2016)
Aranya Goswamy, Sagar Kumashi, Vikash Sehwag, Siddharth Singh, Manny Jain, Kaushik Roy, Mrigank Sharad
Energy Efficient and High Performance Current-Mode Neural Network Circuit using Memristors and Digitally Assisted Analog CMOS Neurons. CoRR (2015)