Certified Robustness to Adversarial Examples with Differential Privacy

9 February 2018

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

50 / 208 papers shown

Title
Enhancing Quantum Adversarial Robustness by Randomized Encodings Weiyuan Gong D. Yuan Weikang Li D. Deng AAML 24 19 0 05 Dec 2022
PiPar: Pipeline Parallelism for Collaborative Machine Learning Zihan Zhang Philip Rodgers Peter Kilpatrick I. Spence Blesson Varghese FedML 43 3 0 01 Dec 2022
Adversarial Rademacher Complexity of Deep Neural Networks Jiancong Xiao Yanbo Fan Ruoyu Sun Zhimin Luo AAML 17 22 0 27 Nov 2022
Invariance-Aware Randomized Smoothing Certificates Jan Schuchardt Stephan Günnemann AAML 28 5 0 25 Nov 2022
Fairness Increases Adversarial Vulnerability Cuong Tran Keyu Zhu Ferdinando Fioretto Pascal Van Hentenryck 34 6 0 21 Nov 2022
Understanding the Vulnerability of Skeleton-based Human Activity Recognition via Black-box Attack Yunfeng Diao He Wang Tianjia Shao Yong-Liang Yang Kun Zhou David C. Hogg Meng Wang AAML 42 7 0 21 Nov 2022
Towards Robust Dataset Learning Yihan Wu Xinda Li Florian Kerschbaum Heng Huang Hongyang R. Zhang DD OOD 49 10 0 19 Nov 2022
Improved techniques for deterministic l2 robustness Sahil Singla S. Feizi AAML 23 9 0 15 Nov 2022
Defending with Errors: Approximate Computing for Robustness of Deep Neural Networks Amira Guesmi Ihsen Alouani Khaled N. Khasawneh M. Baklouti T. Frikha Mohamed Abid Nael B. Abu-Ghazaleh AAML OOD 30 2 0 02 Nov 2022
There is more than one kind of robustness: Fooling Whisper with adversarial examples R. Olivier Bhiksha Raj AAML 40 12 0 26 Oct 2022
Accelerating Certified Robustness Training via Knowledge Transfer Pratik Vaishnavi Kevin Eykholt Amir Rahmati 24 7 0 25 Oct 2022
Evolution of Neural Tangent Kernels under Benign and Adversarial Training Noel Loo Ramin Hasani Alexander Amini Daniela Rus AAML 36 13 0 21 Oct 2022
DE-CROP: Data-efficient Certified Robustness for Pretrained Classifiers Gaurav Kumar Nayak Ruchit Rawal Anirban Chakraborty 19 3 0 17 Oct 2022
Certified Training: Small Boxes are All You Need Mark Niklas Muller Franziska Eckert Marc Fischer Martin Vechev AAML 39 45 0 10 Oct 2022
IvySyn: Automated Vulnerability Discovery in Deep Learning Frameworks Neophytos Christou Di Jin Vaggelis Atlidakis Baishakhi Ray V. Kemerlis 29 13 0 29 Sep 2022
Membership Inference Attacks by Exploiting Loss Trajectory Yiyong Liu Zhengyu Zhao Michael Backes Yang Zhang 27 98 0 31 Aug 2022
DNNShield: Dynamic Randomized Model Sparsification, A Defense Against Adversarial Machine Learning Mohammad Hossein Samavatian Saikat Majumdar Kristin Barber R. Teodorescu AAML 21 2 0 31 Jul 2022
RUSH: Robust Contrastive Learning via Randomized Smoothing Yijiang Pang Boyang Liu Jiayu Zhou OOD AAML 19 1 0 11 Jul 2022
Wild Networks: Exposure of 5G Network Infrastructures to Adversarial Examples Giovanni Apruzzese Rodion Vladimirov A.T. Tastemirova Pavel Laskov AAML 38 15 0 04 Jul 2022
RegMixup: Mixup as a Regularizer Can Surprisingly Improve Accuracy and Out Distribution Robustness Francesco Pinto Harry Yang Ser-Nam Lim Philip Torr P. Dokania UQCV 33 34 0 29 Jun 2022
Increasing Confidence in Adversarial Robustness Evaluations Roland S. Zimmermann Wieland Brendel Florian Tramèr Nicholas Carlini AAML 36 16 0 28 Jun 2022
Riemannian data-dependent randomized smoothing for neural networks certification Pol Labarbarie H. Hajri M. Arnaudon 29 4 0 21 Jun 2022
Transferable Graph Backdoor Attack Shuiqiao Yang Bao Gia Doan Paul Montague O. Vel Tamas Abraham S. Çamtepe Damith C. Ranasinghe S. Kanhere AAML 44 36 0 21 Jun 2022
On the Limitations of Stochastic Pre-processing Defenses Yue Gao Ilia Shumailov Kassem Fawaz Nicolas Papernot AAML SILM 47 31 0 19 Jun 2022
Double Sampling Randomized Smoothing Linyi Li Jiawei Zhang Tao Xie Bo-wen Li AAML 17 23 0 16 Jun 2022
Towards Evading the Limits of Randomized Smoothing: A Theoretical Analysis Raphael Ettedgui Alexandre Araujo Rafael Pinot Y. Chevaleyre Jamal Atif AAML 34 3 0 03 Jun 2022
(De-)Randomized Smoothing for Decision Stump Ensembles Miklós Z. Horváth Mark Niklas Muller Marc Fischer Martin Vechev 30 3 0 27 May 2022
Adversarial Attack on Attackers: Post-Process to Mitigate Black-Box Score-Based Query Attacks Sizhe Chen Zhehao Huang Qinghua Tao Yingwen Wu Cihang Xie X. Huang AAML 110 28 0 24 May 2022
Smooth-Reduce: Leveraging Patches for Improved Certified Robustness Ameya Joshi Minh Pham Minsu Cho Leonid Boytsov Filipe Condessa J. Zico Kolter C. Hegde UQCV AAML 32 2 0 12 May 2022
3DeformRS: Certifying Spatial Deformations on Point Clouds S. GabrielPérez Juan C. Pérez Motasem Alfarra Silvio Giancola Guohao Li 3DPC 32 12 0 12 Apr 2022
Enabling All In-Edge Deep Learning: A Literature Review Praveen Joshi Mohammed Hasanuzzaman Chandra Thapa Haithem Afli T. Scully 43 22 0 07 Apr 2022
SoK: On the Semantic AI Security in Autonomous Driving Junjie Shen Ningfei Wang Ziwen Wan Yunpeng Luo Takami Sato ... Zhenyu Zhong Kang Li Ziming Zhao Chunming Qiao Qi Alfred Chen AAML 23 40 0 10 Mar 2022
Defending Black-box Skeleton-based Human Activity Classifiers He Wang Yunfeng Diao Zichang Tan G. Guo AAML 51 10 0 09 Mar 2022
Differential Privacy Amplification in Quantum and Quantum-inspired Algorithms Armando Angrisani Mina Doosti E. Kashefi 24 12 0 07 Mar 2022
Adversarially Robust Learning with Tolerance H. Ashtiani Vinayak Pathak Ruth Urner AAML 26 9 0 02 Mar 2022
Robust Probabilistic Time Series Forecasting Taeho Yoon Youngsuk Park Ernest K. Ryu Yuyang Wang AAML AI4TS 20 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 54 33 0 23 Feb 2022
Differentially Private Graph Classification with GNNs Tamara T. Mueller Johannes C. Paetzold Chinmay Prabhakar Dmitrii Usynin Daniel Rueckert Georgios Kaissis 50 18 0 05 Feb 2022
Smoothed Embeddings for Certified Few-Shot Learning Mikhail Aleksandrovich Pautov Olesya Kuznetsova Nurislam Tursynbek Aleksandr Petiushko Ivan Oseledets 42 5 0 02 Feb 2022
Boundary Defense Against Black-box Adversarial Attacks Manjushree B. Aithal Xiaohua Li AAML 21 6 0 31 Jan 2022
Certifying Model Accuracy under Distribution Shifts Aounon Kumar Alexander Levine Tom Goldstein S. Feizi OOD 27 7 0 28 Jan 2022
Constrained Gradient Descent: A Powerful and Principled Evasion Attack Against Neural Networks Weiran Lin Keane Lucas Lujo Bauer Michael K. Reiter Mahmood Sharif AAML 31 5 0 28 Dec 2021
Adversarial Attack for Asynchronous Event-based Data Wooju Lee Hyun Myung AAML 22 8 0 27 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 38 21 0 01 Dec 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 49 15 0 19 Nov 2021
Robust and Information-theoretically Safe Bias Classifier against Adversarial Attacks Lijia Yu Xiao-Shan Gao AAML 21 5 0 08 Nov 2021
Training Certifiably Robust Neural Networks with Efficient Local Lipschitz Bounds Yujia Huang Huan Zhang Yuanyuan Shi J Zico Kolter Anima Anandkumar 38 76 0 02 Nov 2021
Combining Diverse Feature Priors Saachi Jain Dimitris Tsipras A. Madry 64 14 0 15 Oct 2021
Combining Differential Privacy and Byzantine Resilience in Distributed SGD R. Guerraoui Nirupam Gupta Rafael Pinot Sébastien Rouault John Stephan FedML 43 4 0 08 Oct 2021
Improving Adversarial Robustness for Free with Snapshot Ensemble Yihao Wang AAML UQCV 17 1 0 07 Oct 2021