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Certified Robustness to Adversarial Examples with Differential Privacy

9 February 2018

Papers citing "Certified Robustness to Adversarial Examples with Differential Privacy"

50 / 567 papers shown

Title
Robust Probabilistic Time Series Forecasting Taeho Yoon Youngsuk Park Ernest K. Ryu Yuyang Wang AAML AI4TS 61 18 0 24 Feb 2022
Differentially Private Speaker Anonymization Ali Shahin Shamsabadi B. M. L. Srivastava A. Bellet Nathalie Vauquier Emmanuel Vincent Mohamed Maouche Marc Tommasi Nicolas Papernot MIACV 148 35 0 23 Feb 2022
Rethinking Machine Learning Robustness via its Link with the Out-of-Distribution Problem Abderrahmen Amich Birhanu Eshete OOD 35 4 0 18 Feb 2022
Holistic Adversarial Robustness of Deep Learning Models Pin-Yu Chen Sijia Liu AAML 105 16 0 15 Feb 2022
Robust Estimation of Discrete Distributions under Local Differential Privacy J. Chhor Flore Sentenac FedML 71 13 0 14 Feb 2022
Towards Assessing and Characterizing the Semantic Robustness of Face Recognition Juan C. Pérez Motasem Alfarra Ali K. Thabet Pablo Arbelaez Guohao Li AAML 72 1 0 10 Feb 2022
Differentially Private Graph Classification with GNNs Tamara T. Mueller Johannes C. Paetzold Chinmay Prabhakar Dmitrii Usynin Daniel Rueckert Georgios Kaissis 88 22 0 05 Feb 2022
ObjectSeeker: Certifiably Robust Object Detection against Patch Hiding Attacks via Patch-agnostic Masking Chong Xiang Alexander Valtchanov Saeed Mahloujifar Prateek Mittal AAML 85 23 0 03 Feb 2022
Certifying Out-of-Domain Generalization for Blackbox Functions Maurice Weber Linyi Li Wei Ping Zhikuan Zhao Yue Liu Ce Zhang OOD 76 15 0 03 Feb 2022
Smoothed Embeddings for Certified Few-Shot Learning Mikhail Aleksandrovich Pautov Olesya Kuznetsova Nurislam Tursynbek Aleksandr Petiushko Ivan Oseledets 96 6 0 02 Feb 2022
An Eye for an Eye: Defending against Gradient-based Attacks with Gradients Hanbin Hong Yuan Hong Yu Kong AAML 65 2 0 02 Feb 2022
Boundary Defense Against Black-box Adversarial Attacks Manjushree B. Aithal Xiaohua Li AAML 76 6 0 31 Jan 2022
Certifying Model Accuracy under Distribution Shifts Aounon Kumar Alexander Levine Tom Goldstein Soheil Feizi OOD 108 7 0 28 Jan 2022
What You See is Not What the Network Infers: Detecting Adversarial Examples Based on Semantic Contradiction Yijun Yang Ruiyuan Gao Yu Li Qiuxia Lai Qiang Xu GAN AAML 111 20 0 24 Jan 2022
Evaluation of Neural Networks Defenses and Attacks using NDCG and Reciprocal Rank Metrics Haya Brama L. Dery Tal Grinshpoun AAML 66 8 0 10 Jan 2022
Rethinking Feature Uncertainty in Stochastic Neural Networks for Adversarial Robustness Hao Yang Min Wang Zhengfei Yu Yun Zhou OOD AAML 57 3 0 01 Jan 2022
On Distinctive Properties of Universal Perturbations Sung Min Park K. Wei Kai Y. Xiao Jungshian Li Aleksander Madry AAML 131 2 0 31 Dec 2021
Constrained Gradient Descent: A Powerful and Principled Evasion Attack Against Neural Networks Weiran Lin Keane Lucas Lujo Bauer Michael K. Reiter Mahmood Sharif AAML 63 5 0 28 Dec 2021
Adversarial Attack for Asynchronous Event-based Data Wooju Lee Hyun Myung AAML 97 8 0 27 Dec 2021
Perlin Noise Improve Adversarial Robustness C. Tang Kun Zhang Chunfang Xing Yong Ding Zengmin Xu AAML 32 4 0 26 Dec 2021
Distributed Machine Learning and the Semblance of Trust Dmitrii Usynin Alexander Ziller Daniel Rueckert Jonathan Passerat-Palmbach Georgios Kaissis 26 1 0 21 Dec 2021
Robust Upper Bounds for Adversarial Training Dimitris Bertsimas Xavier Boix Kimberly Villalobos Carballo D. Hertog AAML 85 0 0 17 Dec 2021
Preemptive Image Robustification for Protecting Users against Man-in-the-Middle Adversarial Attacks Seungyong Moon Gaon An Hyun Oh Song AAML 46 5 0 10 Dec 2021
Differential Privacy in Privacy-Preserving Big Data and Learning: Challenge and Opportunity Honglu Jiang Yifeng Gao S. M. Sarwar Luis GarzaPerez M. Robin 40 10 0 03 Dec 2021
Certified Adversarial Defenses Meet Out-of-Distribution Corruptions: Benchmarking Robustness and Simple Baselines Jiachen Sun Akshay Mehra B. Kailkhura Pin-Yu Chen Dan Hendrycks Jihun Hamm Z. Morley Mao AAML 79 22 0 01 Dec 2021
Resilience from Diversity: Population-based approach to harden models against adversarial attacks Jasser Jasser Ivan I. Garibay AAML 55 1 0 19 Nov 2021
Mate! Are You Really Aware? An Explainability-Guided Testing Framework for Robustness of Malware Detectors Ruoxi Sun Minhui Xue Gareth Tyson Tian Dong Shaofeng Li Shuo Wang Haojin Zhu S. Çamtepe Surya Nepal AAML 116 15 0 19 Nov 2021
A Review of Adversarial Attack and Defense for Classification Methods Yao Li Minhao Cheng Cho-Jui Hsieh T. C. Lee AAML 76 69 0 18 Nov 2021
SmoothMix: Training Confidence-calibrated Smoothed Classifiers for Certified Robustness Jongheon Jeong Sejun Park Minkyu Kim Heung-Chang Lee Do-Guk Kim Jinwoo Shin AAML 85 57 0 17 Nov 2021
HydraGAN A Multi-head, Multi-objective Approach to Synthetic Data Generation Chance N. DeSmet D. Cook 95 0 0 13 Nov 2021
Robust and Information-theoretically Safe Bias Classifier against Adversarial Attacks Lijia Yu Xiao-Shan Gao AAML 116 5 0 08 Nov 2021
Sequential Randomized Smoothing for Adversarially Robust Speech Recognition R. Olivier Bhiksha Raj AAML 116 11 0 05 Nov 2021
Training Certifiably Robust Neural Networks with Efficient Local Lipschitz Bounds Yujia Huang Huan Zhang Yuanyuan Shi J Zico Kolter Anima Anandkumar 105 78 0 02 Nov 2021
Holistic Deep Learning Dimitris Bertsimas Kimberly Villalobos Carballo L. Boussioux M. Li Alex Paskov I. Paskov 83 2 0 29 Oct 2021
10 Security and Privacy Problems in Large Foundation Models Jinyuan Jia Hongbin Liu Neil Zhenqiang Gong 100 7 0 28 Oct 2021
A Dynamical System Perspective for Lipschitz Neural Networks Laurent Meunier Blaise Delattre Alexandre Araujo A. Allauzen 130 56 0 25 Oct 2021
PRECAD: Privacy-Preserving and Robust Federated Learning via Crypto-Aided Differential Privacy Xiaolan Gu Ming Li Lishuang Xiong FedML 62 11 0 22 Oct 2021
Combining Diverse Feature Priors Saachi Jain Dimitris Tsipras Aleksander Madry 113 14 0 15 Oct 2021
Abstract Interpretation of Fixpoint Iterators with Applications to Neural Networks Mark Niklas Muller Marc Fischer Robin Staab Martin Vechev 49 3 0 14 Oct 2021
Boosting the Certified Robustness of L-infinity Distance Nets Bohang Zhang Du Jiang Di He Liwei Wang OOD 93 30 0 13 Oct 2021
A Framework for Verification of Wasserstein Adversarial Robustness Tobias Wegel F. Assion David Mickisch Florens Greßner AAML 45 0 0 13 Oct 2021
Certified Patch Robustness via Smoothed Vision Transformers Hadi Salman Saachi Jain Eric Wong Aleksander Mkadry AAML 120 59 0 11 Oct 2021
Intriguing Properties of Input-dependent Randomized Smoothing Peter Súkeník A. Kuvshinov Stephan Günnemann AAML UQCV 74 22 0 11 Oct 2021
Combining Differential Privacy and Byzantine Resilience in Distributed SGD R. Guerraoui Nirupam Gupta Rafael Pinot Sébastien Rouault John Stephan FedML 77 4 0 08 Oct 2021
DoubleStar: Long-Range Attack Towards Depth Estimation based Obstacle Avoidance in Autonomous Systems Ce Zhou Qiben Yan Yan Shi Lichao Sun AAML 76 26 0 07 Oct 2021
Improving Adversarial Robustness for Free with Snapshot Ensemble Yihao Wang AAML UQCV 36 1 0 07 Oct 2021
Noisy Feature Mixup Soon Hoe Lim N. Benjamin Erichson Francisco Utrera Winnie Xu Michael W. Mahoney AAML 103 38 0 05 Oct 2021
Trustworthy AI: From Principles to Practices Yue Liu Peng Qi Bo Liu Shuai Di Jingen Liu Jiquan Pei Jinfeng Yi Bowen Zhou 213 383 0 04 Oct 2021
Unsolved Problems in ML Safety Dan Hendrycks Nicholas Carlini John Schulman Jacob Steinhardt 287 294 0 28 Sep 2021
Local Intrinsic Dimensionality Signals Adversarial Perturbations Sandamal Weerasinghe T. Alpcan S. Erfani C. Leckie Benjamin I. P. Rubinstein AAML 42 0 0 24 Sep 2021