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2020 – today
- 2024
[j33]Yicheng Liao
, Yufei Li, Minjie Chen, Lars Nordström, Xiongfei Wang, Prateek Mittal, H. Vincent Poor:
Neural Network Design for Impedance Modeling of Power Electronic Systems Based on Latent Features. IEEE Trans. Neural Networks Learn. Syst. 35(5): 5968-5980 (2024)- [c119]Xiangyu Qi, Kaixuan Huang, Ashwinee Panda, Peter Henderson, Mengdi Wang, Prateek Mittal:
Visual Adversarial Examples Jailbreak Aligned Large Language Models. AAAI 2024: 21527-21536 - [c118]Jiachen T. Wang, Prateek Mittal, Ruoxi Jia:
Efficient Data Shapley for Weighted Nearest Neighbor Algorithms. AISTATS 2024: 2557-2565 - [c117]Lei Gao, Giorgos Christopoulos, Prateek Mittal, Ryuji Hirayama, Sriram Subramanian:
StableLev: Data-Driven Stability Enhancement for Multi-Particle Acoustic Levitation. CHI 2024: 202:1-202:11 - [c116]Josue Ortega Caro, Antonio Henrique de Oliveira Fonseca, Syed Asad Rizvi, Matteo Rosati, Christopher L. Averill, James Cross, Prateek Mittal, Emanuele Zappala, Rahul Madhav Dhodapkar, Chadi Abdallah, David van Dijk:
BrainLM: A foundation model for brain activity recordings. ICLR 2024 - [c115]Ashwinee Panda, Christopher A. Choquette-Choo, Zhengming Zhang, Yaoqing Yang, Prateek Mittal:
Teach LLMs to Phish: Stealing Private Information from Language Models. ICLR 2024 - [c114]Xiangyu Qi, Yi Zeng, Tinghao Xie, Pin-Yu Chen, Ruoxi Jia, Prateek Mittal, Peter Henderson:
Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To! ICLR 2024 - [c113]Tong Wu, Ashwinee Panda, Jiachen T. Wang, Prateek Mittal:
Privacy-Preserving In-Context Learning for Large Language Models. ICLR 2024 - [c112]Tinghao Xie, Xiangyu Qi, Ping He, Yiming Li, Jiachen T. Wang, Prateek Mittal:
BaDExpert: Extracting Backdoor Functionality for Accurate Backdoor Input Detection. ICLR 2024 - [c111]Ashwinee Panda, Xinyu Tang, Saeed Mahloujifar, Vikash Sehwag, Prateek Mittal:
A New Linear Scaling Rule for Private Adaptive Hyperparameter Optimization. ICML 2024 - [c110]Boyi Wei, Kaixuan Huang, Yangsibo Huang, Tinghao Xie, Xiangyu Qi, Mengzhou Xia, Prateek Mittal, Mengdi Wang, Peter Henderson:
Assessing the Brittleness of Safety Alignment via Pruning and Low-Rank Modifications. ICML 2024 - [c109]Chong Xiang, Tong Wu, Sihui Dai, Jonathan Petit, Suman Jana, Prateek Mittal:
PatchCURE: Improving Certifiable Robustness, Model Utility, and Computation Efficiency of Adversarial Patch Defenses. USENIX Security Symposium 2024 - [i118]Xinyu Tang, Ashwinee Panda, Milad Nasr, Saeed Mahloujifar, Prateek Mittal:
Private Fine-tuning of Large Language Models with Zeroth-order Optimization. CoRR abs/2401.04343 (2024) - [i117]Jiachen T. Wang, Prateek Mittal, Ruoxi Jia:
Efficient Data Shapley for Weighted Nearest Neighbor Algorithms. CoRR abs/2401.11103 (2024) - [i116]Boyi Wei, Kaixuan Huang, Yangsibo Huang, Tinghao Xie, Xiangyu Qi, Mengzhou Xia, Prateek Mittal, Mengdi Wang, Peter Henderson:
Assessing the Brittleness of Safety Alignment via Pruning and Low-Rank Modifications. CoRR abs/2402.05162 (2024) - [i115]Ashwinee Panda, Christopher A. Choquette-Choo, Zhengming Zhang, Yaoqing Yang, Prateek Mittal:
Teach LLMs to Phish: Stealing Private Information from Language Models. CoRR abs/2403.00871 (2024) - [i114]Sihui Dai, Chong Xiang, Tong Wu, Prateek Mittal:
Position Paper: Beyond Robustness Against Single Attack Types. CoRR abs/2405.01349 (2024) - [i113]Chong Xiang, Tong Wu, Zexuan Zhong, David A. Wagner, Danqi Chen, Prateek Mittal:
Certifiably Robust RAG against Retrieval Corruption. CoRR abs/2405.15556 (2024) - [i112]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) - [i111]Xiangyu Qi, Ashwinee Panda, Kaifeng Lyu, Xiao Ma, Subhrajit Roy, Ahmad Beirami, Prateek Mittal, Peter Henderson:
Safety Alignment Should Be Made More Than Just a Few Tokens Deep. CoRR abs/2406.05946 (2024) - [i110]Jiachen T. Wang, Prateek Mittal, Dawn Song, Ruoxi Jia:
Data Shapley in One Training Run. CoRR abs/2406.11011 (2024) - [i109]Tinghao Xie, Xiangyu Qi, Yi Zeng, Yangsibo Huang, Udari Madhushani Sehwag, Kaixuan Huang, Luxi He, Boyi Wei, Dacheng Li, Ying Sheng, Ruoxi Jia, Bo Li, Kai Li, Danqi Chen, Peter Henderson, Prateek Mittal:
SORRY-Bench: Systematically Evaluating Large Language Model Safety Refusal Behaviors. CoRR abs/2406.14598 (2024) - [i108]Vineet Jagadeesan Nair, Venkatesh Venkataramanan, Priyank Srivastava, Partha S. Sarker, Anurag Srivastava, Laurentiu D. Marinovici, Jun Zha, Christopher Irwin, Prateek Mittal, John Williams, H. Vincent Poor, Anuradha M. Annaswamy:
Resilience of the Electric Grid through Trustable IoT-Coordinated Assets. CoRR abs/2406.14861 (2024) - [i107]Ashwinee Panda, Berivan Isik, Xiangyu Qi, Sanmi Koyejo, Tsachy Weissman, Prateek Mittal:
Lottery Ticket Adaptation: Mitigating Destructive Interference in LLMs. CoRR abs/2406.16797 (2024) - 2023
- [j32]NagaSree Keerthi Pujari, Srinivas Soumitri Miriyala, Prateek Mittal, Kishalay Mitra:
Better wind forecasting using Evolutionary Neural Architecture search driven Green Deep Learning. Expert Syst. Appl. 214: 119063 (2023) - [j31]Liang Wang, Hyojoon Kim, Prateek Mittal, Jennifer Rexford:
RAVEN: Stateless Rapid IP Address Variation for Enterprise Networks. Proc. Priv. Enhancing Technol. 2023(3): 194-210 (2023) - [c108]Xiangyu Qi, Tinghao Xie, Yiming Li, Saeed Mahloujifar, Prateek Mittal:
Revisiting the Assumption of Latent Separability for Backdoor Defenses. ICLR 2023 - [c107]Sihui Dai, Saeed Mahloujifar, Chong Xiang, Vikash Sehwag, Pin-Yu Chen, Prateek Mittal:
MultiRobustBench: Benchmarking Robustness Against Multiple Attacks. ICML 2023: 6760-6785 - [c106]Milad Nasr, Saeed Mahloujifar, Xinyu Tang, Prateek Mittal, Amir Houmansadr:
Effectively Using Public Data in Privacy Preserving Machine Learning. ICML 2023: 25718-25732 - [c105]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 - [c104]Jacob Alexander Markson Brown, Xi Jiang, Van Hong Tran, Arjun Nitin Bhagoji, Nguyen Phong Hoang, Nick Feamster, Prateek Mittal, Vinod Yegneswaran:
Augmenting Rule-based DNS Censorship Detection at Scale with Machine Learning. KDD 2023: 3750-3761 - [c103]Sihui Dai, Wenxin Ding, Arjun Nitin Bhagoji, Daniel Cullina, Heather Zheng, Ben Zhao, Prateek Mittal:
Characterizing the Optimal 0-1 Loss for Multi-class Classification with a Test-time Attacker. NeurIPS 2023 - [c102]Xinyu Tang, Ashwinee Panda, Vikash Sehwag, Prateek Mittal:
Differentially Private Image Classification by Learning Priors from Random Processes. NeurIPS 2023 - [c101]Jiachen T. Wang, Yuqing Zhu, Yu-Xiang Wang, Ruoxi Jia, Prateek Mittal:
A Privacy-Friendly Approach to Data Valuation. NeurIPS 2023 - [c100]Jiachen T. Wang, Saeed Mahloujifar, Tong Wu, Ruoxi Jia, Prateek Mittal:
A Randomized Approach to Tight Privacy Accounting. NeurIPS 2023 - [c99]Edoardo Debenedetti, Vikash Sehwag, Prateek Mittal:
A Light Recipe to Train Robust Vision Transformers. SaTML 2023: 225-253 - [c98]Chong Xiang, Alexander Valtchanov, Saeed Mahloujifar, Prateek Mittal:
ObjectSeeker: Certifiably Robust Object Detection against Patch Hiding Attacks via Patch-agnostic Masking. SP 2023: 1329-1347 - [c97]Xiangyu Qi, Tinghao Xie, Jiachen T. Wang, Tong Wu, Saeed Mahloujifar, Prateek Mittal:
Towards A Proactive ML Approach for Detecting Backdoor Poison Samples. USENIX Security Symposium 2023: 1685-1702 - [c96]Grace H. Cimaszewski, Henry Birge-Lee, Liang Wang, Jennifer Rexford, Prateek Mittal:
How Effective is Multiple-Vantage-Point Domain Control Validation? USENIX Security Symposium 2023: 5701-5718 - [i106]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) - [i105]Jacob Alexander Markson Brown, Xi Jiang, Van Hong Tran, Arjun Nitin Bhagoji, Nguyen Phong Hoang, Nick Feamster, Prateek Mittal, Vinod Yegneswaran:
Augmenting Rule-based DNS Censorship Detection at Scale with Machine Learning. CoRR abs/2302.02031 (2023) - [i104]Grace H. Cimaszewski, Henry Birge-Lee, Liang Wang, Jennifer Rexford, Prateek Mittal:
How Effective is Multiple-Vantage-Point Domain Control Validation? CoRR abs/2302.08000 (2023) - [i103]Sihui Dai, Wenxin Ding, Arjun Nitin Bhagoji, Daniel Cullina, Ben Y. Zhao, Haitao Zheng, Prateek Mittal:
Characterizing the Optimal 0-1 Loss for Multi-class Classification with a Test-time Attacker. CoRR abs/2302.10722 (2023) - [i102]Sihui Dai, Saeed Mahloujifar, Chong Xiang, Vikash Sehwag, Pin-Yu Chen, Prateek Mittal:
MultiRobustBench: Benchmarking Robustness Against Multiple Attacks. CoRR abs/2302.10980 (2023) - [i101]Watson Jia, Mona Wang, Liang Wang, Prateek Mittal:
QUICstep: Circumventing QUIC-based Censorship. CoRR abs/2304.01073 (2023) - [i100]Jiachen T. Wang, Saeed Mahloujifar, Tong Wu, Ruoxi Jia, Prateek Mittal:
A Randomized Approach for Tight Privacy Accounting. CoRR abs/2304.07927 (2023) - [i99]Ashwinee Panda, Tong Wu, Jiachen T. Wang, Prateek Mittal:
Differentially Private In-Context Learning. CoRR abs/2305.01639 (2023) - [i98]Xinyu Tang, Ashwinee Panda, Vikash Sehwag, Prateek Mittal:
Differentially Private Image Classification by Learning Priors from Random Processes. CoRR abs/2306.06076 (2023) - [i97]Xiangyu Qi, Kaixuan Huang, Ashwinee Panda, Mengdi Wang, Prateek Mittal:
Visual Adversarial Examples Jailbreak Large Language Models. CoRR abs/2306.13213 (2023) - [i96]Pengcheng Fang, Peng Gao, Yun Peng, Qingzhao Zhang, Tao Xie, Dawn Song, Prateek Mittal, Sanjeev R. Kulkarni, Zhuotao Liu, Xusheng Xiao:
CONTRACTFIX: A Framework for Automatically Fixing Vulnerabilities in Smart Contracts. CoRR abs/2307.08912 (2023) - [i95]Tinghao Xie, Xiangyu Qi, Ping He, Yiming Li, Jiachen T. Wang, Prateek Mittal:
BaDExpert: Extracting Backdoor Functionality for Accurate Backdoor Input Detection. CoRR abs/2308.12439 (2023) - [i94]Jiachen T. Wang, Yuqing Zhu, Yu-Xiang Wang, Ruoxi Jia, Prateek Mittal:
Threshold KNN-Shapley: A Linear-Time and Privacy-Friendly Approach to Data Valuation. CoRR abs/2308.15709 (2023) - [i93]Xiangyu Qi, Yi Zeng, Tinghao Xie, Pin-Yu Chen, Ruoxi Jia, Prateek Mittal, Peter Henderson:
Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To! CoRR abs/2310.03693 (2023) - [i92]Chong Xiang, Tong Wu, Sihui Dai, Jonathan Petit, Suman Jana, Prateek Mittal:
PatchCURE: Improving Certifiable Robustness, Model Utility, and Computation Efficiency of Adversarial Patch Defenses. CoRR abs/2310.13076 (2023) - 2022
- [j30]Liang Wang, Prateek Mittal, Jennifer Rexford:
Data-plane security applications in adversarial settings. Comput. Commun. Rev. 52(2): 2-9 (2022) - [j29]David Marco Sommer, Liwei Song, Sameer Wagh, Prateek Mittal:
Athena: Probabilistic Verification of Machine Unlearning. Proc. Priv. Enhancing Technol. 2022(3): 268-290 (2022) - [j28]Mona Wang, Anunay Kulshrestha, Liang Wang, Prateek Mittal:
Leveraging strategic connection migration-powered traffic splitting for privacy. Proc. Priv. Enhancing Technol. 2022(3): 498-515 (2022) - [j27]Xinyu Tang, Milad Nasr, Saeed Mahloujifar, Virat Shejwalkar, Liwei Song, Amir Houmansadr, Prateek Mittal:
Machine Learning with Differentially Private Labels: Mechanisms and Frameworks. Proc. Priv. Enhancing Technol. 2022(4): 332-350 (2022) - [c95]Yushan Liu, Xiaokui Shu, Yixin Sun, Jiyong Jang, Prateek Mittal:
RAPID: Real-Time Alert Investigation with Context-aware Prioritization for Efficient Threat Discovery. ACSAC 2022: 827-840 - [c94]Ashwinee Panda, Saeed Mahloujifar, Arjun Nitin Bhagoji, Supriyo Chakraborty, Prateek Mittal:
SparseFed: Mitigating Model Poisoning Attacks in Federated Learning with Sparsification. AISTATS 2022: 7587-7624 - [c93]Tong Wu, Tianhao Wang, Vikash Sehwag, Saeed Mahloujifar, Prateek Mittal:
Just Rotate it: Deploying Backdoor Attacks via Rotation Transformation. AISec@CCS 2022: 91-102 - [c92]Anna Harbluk Lorimer, Nick Feamster, Prateek Mittal:
Poster: Investigating QUIC's Potential Impact on Censorship Circumvention. CCS 2022: 3403-3405 - [c91]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 - [c90]Zhengming Zhang, Ashwinee Panda, Linyue Song, Yaoqing Yang, Michael W. Mahoney, Prateek Mittal, Kannan Ramchandran, Joseph Gonzalez:
Neurotoxin: Durable Backdoors in Federated Learning. ICML 2022: 26429-26446 - [c89]Laurent Chuat, Cyrill Krähenbühl, Prateek Mittal, Adrian Perrig:
F-PKI: Enabling Innovation and Trust Flexibility in the HTTPS Public-Key Infrastructure. NDSS 2022 - [c88]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 - [c87]Sihui Dai, Saeed Mahloujifar, Prateek Mittal:
Formulating Robustness Against Unforeseen Attacks. NeurIPS 2022 - [c86]Jiachen T. Wang, Saeed Mahloujifar, Shouda Wang, Ruoxi Jia, Prateek Mittal:
Renyi Differential Privacy of Propose-Test-Release and Applications to Private and Robust Machine Learning. NeurIPS 2022 - [c85]Sihui Dai, Saeed Mahloujifar, Prateek Mittal:
Parameterizing Activation Functions for Adversarial Robustness. SP (Workshops) 2022: 80-87 - [c84]Jean-Pierre Smith, Luca Dolfi, Prateek Mittal, Adrian Perrig:
QCSD: A QUIC Client-Side Website-Fingerprinting Defence Framework. USENIX Security Symposium 2022: 771-789 - [c83]Xinyu Tang, Saeed Mahloujifar, Liwei Song, Virat Shejwalkar, Milad Nasr, Amir Houmansadr, Prateek Mittal:
Mitigating Membership Inference Attacks by Self-Distillation Through a Novel Ensemble Architecture. USENIX Security Symposium 2022: 1433-1450 - [c82]Chong Xiang, Saeed Mahloujifar, Prateek Mittal:
PatchCleanser: Certifiably Robust Defense against Adversarial Patches for Any Image Classifier. USENIX Security Symposium 2022: 2065-2082 - [c81]Henry Birge-Lee, Joel Wanner, Grace H. Cimaszewski, Jonghoon Kwon, Liang Wang, François Wirz, Prateek Mittal, Adrian Perrig, Yixin Sun:
Creating a Secure Underlay for the Internet. USENIX Security Symposium 2022: 2601-2618 - [i91]Chong Xiang, Alexander Valtchanov, Saeed Mahloujifar, Prateek Mittal:
ObjectSeeker: Certifiably Robust Object Detection against Patch Hiding Attacks via Patch-agnostic Masking. CoRR abs/2202.01811 (2022) - [i90]Ryan Amos, Roland Maio, Prateek Mittal:
Reviews in motion: a large scale, longitudinal study of review recommendations on Yelp. CoRR abs/2202.09005 (2022) - [i89]Jordan Holland, Paul Schmitt, Prateek Mittal, Nick Feamster:
Towards Reproducible Network Traffic Analysis. CoRR abs/2203.12410 (2022) - [i88]Sihui Dai, Saeed Mahloujifar, Prateek Mittal:
Formulating Robustness Against Unforeseen Attacks. CoRR abs/2204.13779 (2022) - [i87]Mona Wang, Anunay Kulshrestha, Liang Wang, Prateek Mittal:
Leveraging strategic connection migration-powered traffic splitting for privacy. CoRR abs/2205.03326 (2022) - [i86]Xiangyu Qi, Tinghao Xie, Saeed Mahloujifar, Prateek Mittal:
Circumventing Backdoor Defenses That Are Based on Latent Separability. CoRR abs/2205.13613 (2022) - [i85]Xiangyu Qi, Tinghao Xie, Saeed Mahloujifar, Prateek Mittal:
Fight Poison with Poison: Detecting Backdoor Poison Samples via Decoupling Benign Correlations. CoRR abs/2205.13616 (2022) - [i84]Henry Birge-Lee, Joel Wanner, Grace H. Cimaszewski, Jonghoon Kwon, Liang Wang, François Wirz, Prateek Mittal, Adrian Perrig, Yixin Sun:
Creating a Secure Underlay for the Internet. CoRR abs/2206.06879 (2022) - [i83]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) - [i82]Zhengming Zhang, Ashwinee Panda, Linyue Song, Yaoqing Yang, Michael W. Mahoney, Joseph E. Gonzalez, Kannan Ramchandran, Prateek Mittal:
Neurotoxin: Durable Backdoors in Federated Learning. CoRR abs/2206.10341 (2022) - [i81]Tong Wu, Tianhao Wang, Vikash Sehwag, Saeed Mahloujifar, Prateek Mittal:
Just Rotate it: Deploying Backdoor Attacks via Rotation Transformation. CoRR abs/2207.10825 (2022) - [i80]Edoardo Debenedetti, Vikash Sehwag, Prateek Mittal:
A Light Recipe to Train Robust Vision Transformers. CoRR abs/2209.07399 (2022) - [i79]Jiachen T. Wang, Saeed Mahloujifar, Shouda Wang, Ruoxi Jia, Prateek Mittal:
Renyi Differential Privacy of Propose-Test-Release and Applications to Private and Robust Machine Learning. CoRR abs/2209.07716 (2022) - [i78]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
- [j26]Sameer Wagh, Xi He, Ashwin Machanavajjhala, Prateek Mittal:
DP-cryptography: marrying differential privacy and cryptography in emerging applications. Commun. ACM 64(2): 84-93 (2021) - [j25]Yixin Sun, Maria Apostolaki, Henry Birge-Lee, Laurent Vanbever, Jennifer Rexford, Mung Chiang, Prateek Mittal:
Securing internet applications from routing attacks. Commun. ACM 64(6): 86-96 (2021) - [j24]Peter Kairouz, H. Brendan McMahan, Brendan Avent, Aurélien Bellet, Mehdi Bennis, Arjun Nitin Bhagoji, Kallista A. Bonawitz, Zachary Charles, Graham Cormode, Rachel Cummings, Rafael G. L. D'Oliveira, Hubert Eichner, Salim El Rouayheb, David Evans, Josh Gardner, Zachary Garrett, Adrià Gascón, Badih Ghazi, Phillip B. Gibbons, Marco Gruteser, Zaïd Harchaoui, Chaoyang He, Lie He, Zhouyuan Huo, Ben Hutchinson, Justin Hsu, Martin Jaggi, Tara Javidi, Gauri Joshi, Mikhail Khodak, Jakub Konecný, Aleksandra Korolova, Farinaz Koushanfar, Sanmi Koyejo, Tancrède Lepoint, Yang Liu, Prateek Mittal, Mehryar Mohri, Richard Nock, Ayfer Özgür, Rasmus Pagh, Hang Qi, Daniel Ramage, Ramesh Raskar, Mariana Raykova, Dawn Song, Weikang Song, Sebastian U. Stich, Ziteng Sun, Ananda Theertha Suresh, Florian Tramèr, Praneeth Vepakomma, Jianyu Wang, Li Xiong, Zheng Xu, Qiang Yang, Felix X. Yu, Han Yu, Sen Zhao:
Advances and Open Problems in Federated Learning. Found. Trends Mach. Learn. 14(1-2): 1-210 (2021) - [j23]Sameer Wagh, Shruti Tople, Fabrice Benhamouda, Eyal Kushilevitz, Prateek Mittal, Tal Rabin:
Falcon: Honest-Majority Maliciously Secure Framework for Private Deep Learning. Proc. Priv. Enhancing Technol. 2021(1): 188-208 (2021) - [j22]Jean-Pierre Smith, Prateek Mittal, Adrian Perrig:
Website Fingerprinting in the Age of QUIC. Proc. Priv. Enhancing Technol. 2021(2): 48-69 (2021) - [j21]Anatoly Shusterman, Zohar Avraham, Eliezer Croitoru, Yarden Haskal, Lachlan Kang, Dvir Levi, Yosef Meltser, Prateek Mittal, Yossi Oren, Yuval Yarom:
Website Fingerprinting Through the Cache Occupancy Channel and its Real World Practicality. IEEE Trans. Dependable Secur. Comput. 18(5): 2042-2060 (2021) - [c80]Chong Xiang, Prateek Mittal:
DetectorGuard: Provably Securing Object Detectors against Localized Patch Hiding Attacks. CCS 2021: 3177-3196 - [c79]Jordan Holland, Paul Schmitt, Nick Feamster, Prateek Mittal:
New Directions in Automated Traffic Analysis. CCS 2021: 3366-3383 - [c78]Peng Gao, Fei Shao, Xiaoyuan Liu, Xusheng Xiao, Zheng Qin, Fengyuan Xu, Prateek Mittal, Sanjeev R. Kulkarni, Dawn Song:
Enabling Efficient Cyber Threat Hunting With Cyber Threat Intelligence. ICDE 2021: 193-204 - [c77]Peng Gao, Fei Shao, Xiaoyuan Liu, Xusheng Xiao, Haoyuan Liu, Zheng Qin, Fengyuan Xu, Prateek Mittal, Sanjeev R. Kulkarni, Dawn Song:
A System for Efficiently Hunting for Cyber Threats in Computer Systems Using Threat Intelligence. ICDE 2021: 2705-2708 - [c76]Vikash Sehwag, Mung Chiang, Prateek Mittal:
SSD: A Unified Framework for Self-Supervised Outlier Detection. ICLR 2021 - [c75]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 - [c74]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 - [c73]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: 2237-2254 - [c72]Liwei Song, Prateek Mittal:
Systematic Evaluation of Privacy Risks of Machine Learning Models. USENIX Security Symposium 2021: 2615-2632 - [c71]Henry Birge-Lee, Liang Wang, Daniel McCarney, Roland Shoemaker, Jennifer Rexford, Prateek Mittal:
Experiences Deploying Multi-Vantage-Point Domain Validation at Let's Encrypt. USENIX Security Symposium 2021: 4311-4327 - [i77]Peng Gao, Fei Shao, Xiaoyuan Liu, Xusheng Xiao, Haoyuan Liu, Zheng Qin, Fengyuan Xu, Prateek Mittal, Sanjeev R. Kulkarni, Dawn Song:
A System for Efficiently Hunting for Cyber Threats in Computer Systems Using Threat Intelligence. CoRR abs/2101.06761 (2021) - [i76]Chong Xiang, Prateek Mittal:
DetectorGuard: Provably Securing Object Detectors against Localized Patch Hiding Attacks. CoRR abs/2102.02956 (2021) - [i75]Vikash Sehwag, Mung Chiang, Prateek Mittal:
SSD: A Unified Framework for Self-Supervised Outlier Detection. CoRR abs/2103.12051 (2021) - [i74]Arjun Nitin Bhagoji, Daniel Cullina, Vikash Sehwag, Prateek Mittal:
Lower Bounds on Cross-Entropy Loss in the Presence of Test-time Adversaries. CoRR abs/2104.08382 (2021) - [i73]Vikash Sehwag, Saeed Mahloujifar, Tinashe Handina, Sihui Dai, Chong Xiang, Mung Chiang, Prateek Mittal:
Improving Adversarial Robustness Using Proxy Distributions. CoRR abs/2104.09425 (2021) - [i72]Chong Xiang, Prateek Mittal:
PatchGuard++: Efficient Provable Attack Detection against Adversarial Patches. CoRR abs/2104.12609 (2021) - [i71]Laurent Chuat, Cyrill Krähenbühl, Prateek Mittal, Adrian Perrig:
F-PKI: Enabling Innovation and Trust Flexibility in the HTTPS Public-Key Infrastructure. CoRR abs/2108.08581 (2021) - [i70]Chong Xiang, Saeed Mahloujifar, Prateek Mittal:
PatchCleanser: Certifiably Robust Defense against Adversarial Patches for Any Image Classifier. CoRR abs/2108.09135 (2021) - [i69]Sihui Dai, Saeed Mahloujifar, Prateek Mittal:
Parameterizing Activation Functions for Adversarial Robustness. CoRR abs/2110.05626 (2021) - [i68]Xinyu Tang, Saeed Mahloujifar, Liwei Song, Virat Shejwalkar, Milad Nasr, Amir Houmansadr, Prateek Mittal:
Mitigating Membership Inference Attacks by Self-Distillation Through a Novel Ensemble Architecture. CoRR abs/2110.08324 (2021) - [i67]Liang Wang, Prateek Mittal, Jennifer Rexford:
Data-Plane Security Applications in Adversarial Settings. CoRR abs/2111.02268 (2021) - [i66]Ashwinee Panda, Saeed Mahloujifar, Arjun Nitin Bhagoji, Supriyo Chakraborty, Prateek Mittal:
SparseFed: Mitigating Model Poisoning Attacks in Federated Learning with Sparsification. CoRR abs/2112.06274 (2021) - 2020
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