On Evaluating Adversarial Robustness

18 February 2019

Wieland Brendel

Papers citing "On Evaluating Adversarial Robustness"

50 / 201 papers shown

Title
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
Adversarial Policies Beat Superhuman Go AIs T. T. Wang Adam Gleave Tom Tseng Kellin Pelrine Nora Belrose ... Michael Dennis Yawen Duan V. Pogrebniak Sergey Levine Stuart Russell AAML 13 21 0 01 Nov 2022
Private and Reliable Neural Network Inference Nikola Jovanović Marc Fischer Samuel Steffen Martin Vechev 22 14 0 27 Oct 2022
Multi-view Representation Learning from Malware to Defend Against Adversarial Variants Junjie Hu Mohammadreza Ebrahimi Weifeng Li Xin Li Hsinchun Chen AAML 21 2 0 25 Oct 2022
Causal Information Bottleneck Boosts Adversarial Robustness of Deep Neural Network Hua Hua Jun Yan Xi Fang Weiquan Huang Huilin Yin Wancheng Ge AAML 25 1 0 25 Oct 2022
Scaling Laws for Reward Model Overoptimization Leo Gao John Schulman Jacob Hilton ALM 41 489 0 19 Oct 2022
On the Adversarial Robustness of Mixture of Experts J. Puigcerver Rodolphe Jenatton C. Riquelme Pranjal Awasthi Srinadh Bhojanapalli OOD AAML MoE 48 18 0 19 Oct 2022
Scaling Adversarial Training to Large Perturbation Bounds Sravanti Addepalli Samyak Jain Gaurang Sriramanan R. Venkatesh Babu AAML 33 22 0 18 Oct 2022
Strength-Adaptive Adversarial Training Chaojian Yu Dawei Zhou Li Shen Jun Yu Bo Han Biwei Huang Nannan Wang Tongliang Liu OOD 17 2 0 04 Oct 2022
Perceptual Attacks of No-Reference Image Quality Models with Human-in-the-Loop Weixia Zhang Dingquan Li Xiongkuo Min Guangtao Zhai Guodong Guo Xiaokang Yang Kede Ma OOD 47 34 0 03 Oct 2022
A Closer Look at Evaluating the Bit-Flip Attack Against Deep Neural Networks Kevin Hector Mathieu Dumont Pierre-Alain Moëllic J. Dutertre AAML 27 4 0 28 Sep 2022
AdvDO: Realistic Adversarial Attacks for Trajectory Prediction Yulong Cao Chaowei Xiao Anima Anandkumar Danfei Xu Marco Pavone AAML 32 64 0 19 Sep 2022
A Scalable, Interpretable, Verifiable & Differentiable Logic Gate Convolutional Neural Network Architecture From Truth Tables Adrien Benamira Tristan Guérand Thomas Peyrin Trevor Yap Bryan Hooi 40 1 0 18 Aug 2022
DNNShield: Dynamic Randomized Model Sparsification, A Defense Against Adversarial Machine Learning Mohammad Hossein Samavatian Saikat Majumdar Kristin Barber R. Teodorescu AAML 24 2 0 31 Jul 2022
Discriminator-Weighted Offline Imitation Learning from Suboptimal Demonstrations Haoran Xu Xianyuan Zhan Honglei Yin Huiling Qin OffRL 26 66 0 20 Jul 2022
Invariant Feature Learning for Generalized Long-Tailed Classification Kaihua Tang Mingyuan Tao Jiaxin Qi Zhenguang Liu Hanwang Zhang VLM 32 53 0 19 Jul 2022
Provably Adversarially Robust Nearest Prototype Classifiers Václav Voráček Matthias Hein AAML 20 11 0 14 Jul 2022
Adversarial Robustness Assessment of NeuroEvolution Approaches Inês Valentim Nuno Lourenço Nuno Antunes AAML 34 1 0 12 Jul 2022
Wild Networks: Exposure of 5G Network Infrastructures to Adversarial Examples Giovanni Apruzzese Rodion Vladimirov A.T. Tastemirova Pavel Laskov AAML 40 15 0 04 Jul 2022
Efficient Adversarial Training With Data Pruning Maximilian Kaufmann Yiren Zhao Ilia Shumailov Robert D. Mullins Nicolas Papernot AAML 42 7 0 01 Jul 2022
Threat Assessment in Machine Learning based Systems L. Tidjon Foutse Khomh 27 17 0 30 Jun 2022
Increasing Confidence in Adversarial Robustness Evaluations Roland S. Zimmermann Wieland Brendel Florian Tramèr Nicholas Carlini AAML 41 16 0 28 Jun 2022
Certified Robustness in Federated Learning Motasem Alfarra Juan C. Pérez Egor Shulgin Peter Richtárik Guohao Li AAML FedML 23 7 0 06 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
Learning to Ignore Adversarial Attacks Yiming Zhang Yan Zhou Samuel Carton Chenhao Tan 59 2 0 23 May 2022
3DeformRS: Certifying Spatial Deformations on Point Clouds S. GabrielPérez Juan C. Pérez Motasem Alfarra Silvio Giancola Guohao Li 3DPC 34 12 0 12 Apr 2022
Improving Adversarial Transferability via Neuron Attribution-Based Attacks Jianping Zhang Weibin Wu Jen-tse Huang Yizhan Huang Wenxuan Wang Yuxin Su Michael R. Lyu AAML 45 130 0 31 Mar 2022
Robustness Analysis of Classification Using Recurrent Neural Networks with Perturbed Sequential Input Guangyi Liu Arash A. Amini Martin Takáč N. Motee 31 4 0 10 Mar 2022
Evaluating the Adversarial Robustness of Adaptive Test-time Defenses Francesco Croce Sven Gowal T. Brunner Evan Shelhamer Matthias Hein A. Cemgil TTA AAML 181 68 0 28 Feb 2022
Robustness and Accuracy Could Be Reconcilable by (Proper) Definition Tianyu Pang Min Lin Xiao Yang Junyi Zhu Shuicheng Yan 32 120 0 21 Feb 2022
StratDef: Strategic Defense Against Adversarial Attacks in ML-based Malware Detection Aqib Rashid Jose Such AAML 24 6 0 15 Feb 2022
Holistic Adversarial Robustness of Deep Learning Models Pin-Yu Chen Sijia Liu AAML 51 16 0 15 Feb 2022
Deadwooding: Robust Global Pruning for Deep Neural Networks Sawinder Kaur Ferdinando Fioretto Asif Salekin 27 4 0 10 Feb 2022
Layer-wise Regularized Adversarial Training using Layers Sustainability Analysis (LSA) framework Mohammad Khalooei M. Homayounpour M. Amirmazlaghani AAML 25 3 0 05 Feb 2022
On Adversarial Robustness of Trajectory Prediction for Autonomous Vehicles Qingzhao Zhang Shengtuo Hu Jiachen Sun Qi Alfred Chen Z. Morley Mao AAML 43 133 0 13 Jan 2022
Feature Space Hijacking Attacks against Differentially Private Split Learning Grzegorz Gawron P. Stubbings AAML 27 20 0 11 Jan 2022
On Distinctive Properties of Universal Perturbations Sung Min Park K. Wei Kai Y. Xiao Jungshian Li A. Madry AAML 22 2 0 31 Dec 2021
Single-Shot Black-Box Adversarial Attacks Against Malware Detectors: A Causal Language Model Approach Junjie Hu Mohammadreza Ebrahimi Hsinchun Chen AAML 18 11 0 03 Dec 2021
A Unified Framework for Adversarial Attack and Defense in Constrained Feature Space Thibault Simonetto Salijona Dyrmishi Salah Ghamizi Maxime Cordy Yves Le Traon AAML 24 21 0 02 Dec 2021
Graph Robustness Benchmark: Benchmarking the Adversarial Robustness of Graph Machine Learning Qinkai Zheng Xu Zou Yuxiao Dong Yukuo Cen Da Yin Jiarong Xu Yang Yang Jie Tang OOD AAML 30 50 0 08 Nov 2021
WaveFake: A Data Set to Facilitate Audio Deepfake Detection Joel Frank Lea Schonherr DiffM 132 125 0 04 Nov 2021
LTD: Low Temperature Distillation for Robust Adversarial Training Erh-Chung Chen Che-Rung Lee AAML 27 26 0 03 Nov 2021
FL-WBC: Enhancing Robustness against Model Poisoning Attacks in Federated Learning from a Client Perspective Jingwei Sun Ang Li Louis DiValentin Amin Hassanzadeh Yiran Chen H. Li FedML OOD AAML 36 76 0 26 Oct 2021
EvadeDroid: A Practical Evasion Attack on Machine Learning for Black-box Android Malware Detection Hamid Bostani Veelasha Moonsamy AAML 38 51 0 07 Oct 2021
Simple Post-Training Robustness Using Test Time Augmentations and Random Forest Gilad Cohen Raja Giryes AAML 40 4 0 16 Sep 2021
On the regularized risk of distributionally robust learning over deep neural networks Camilo A. Garcia Trillos Nicolas García Trillos OOD 45 10 0 13 Sep 2021
Morphence: Moving Target Defense Against Adversarial Examples Abderrahmen Amich Birhanu Eshete AAML 27 24 0 31 Aug 2021
On the Exploitability of Audio Machine Learning Pipelines to Surreptitious Adversarial Examples Adelin Travers Lorna Licollari Guanghan Wang Varun Chandrasekaran Adam Dziedzic David Lie Nicolas Papernot AAML 35 3 0 03 Aug 2021
Detecting Adversarial Examples Is (Nearly) As Hard As Classifying Them Florian Tramèr AAML 30 65 0 24 Jul 2021
Towards Robust General Medical Image Segmentation Laura Alexandra Daza Juan C. Pérez Pablo Arbelaez OOD 31 25 0 09 Jul 2021