Mitigating Adversarial Effects Through Randomization

6 November 2017

Cihang Xie

Papers citing "Mitigating Adversarial Effects Through Randomization"

50 / 252 papers shown

Title
Multi-granularity Textual Adversarial Attack with Behavior Cloning Yangyi Chen Jingtong Su Wei Wei AAML 22 32 0 09 Sep 2021
SEC4SR: A Security Analysis Platform for Speaker Recognition Guangke Chen Zhe Zhao Fu Song Sen Chen Lingling Fan Yang Liu AAML 35 12 0 04 Sep 2021
Impact of Attention on Adversarial Robustness of Image Classification Models Prachi Agrawal Narinder Singh Punn S. K. Sonbhadra Sonali Agarwal AAML 24 6 0 02 Sep 2021
Meta Gradient Adversarial Attack Zheng Yuan Jie Zhang Yunpei Jia Chuanqi Tan Tao Xue Shiguang Shan AAML 54 78 0 09 Aug 2021
On the Robustness of Domain Adaption to Adversarial Attacks Liyuan Zhang Yuhang Zhou Lei Zhang OOD AAML 10 2 0 04 Aug 2021
Hybrid Classical-Quantum Deep Learning Models for Autonomous Vehicle Traffic Image Classification Under Adversarial Attack Reek Majumder S. Khan Fahim Ahmed Zadid Khan Frank Ngeni G. Comert Judith Mwakalonge Dimitra Michalaka M. Chowdhury AAML 21 13 0 02 Aug 2021
GradDiv: Adversarial Robustness of Randomized Neural Networks via Gradient Diversity Regularization Sungyoon Lee Hoki Kim Jaewook Lee AAML 37 52 0 06 Jul 2021
Adversarial Visual Robustness by Causal Intervention Kaihua Tang Ming Tao Hanwang Zhang CML AAML 32 21 0 17 Jun 2021
Taxonomy of Machine Learning Safety: A Survey and Primer Sina Mohseni Haotao Wang Zhiding Yu Chaowei Xiao Zhangyang Wang J. Yadawa 31 31 0 09 Jun 2021
Sparta: Spatially Attentive and Adversarially Robust Activation Qing Guo Felix Juefei Xu Changqing Zhou Wei Feng Yang Liu Song Wang AAML 43 4 0 18 May 2021
Salient Feature Extractor for Adversarial Defense on Deep Neural Networks Jinyin Chen Ruoxi Chen Haibin Zheng Zhaoyan Ming Wenrong Jiang Chen Cui AAML 25 10 0 14 May 2021
Deep Image Destruction: Vulnerability of Deep Image-to-Image Models against Adversarial Attacks Jun-Ho Choi Huan Zhang Jun-Hyuk Kim Cho-Jui Hsieh Jong-Seok Lee VLM 29 7 0 30 Apr 2021
Random Noise Defense Against Query-Based Black-Box Attacks Zeyu Qin Yanbo Fan H. Zha Baoyuan Wu AAML 27 60 0 23 Apr 2021
Staircase Sign Method for Boosting Adversarial Attacks Qilong Zhang Xiaosu Zhu Jingkuan Song Lianli Gao Heng Tao Shen AAML 43 13 0 20 Apr 2021
Relating Adversarially Robust Generalization to Flat Minima David Stutz Matthias Hein Bernt Schiele OOD 43 65 0 09 Apr 2021
Can audio-visual integration strengthen robustness under multimodal attacks? Yapeng Tian Chenliang Xu AAML 38 37 0 05 Apr 2021
Mitigating Gradient-based Adversarial Attacks via Denoising and Compression Rehana Mahfuz R. Sahay Aly El Gamal AAML 22 3 0 03 Apr 2021
Enhancing the Transferability of Adversarial Attacks through Variance Tuning Xiaosen Wang Kun He AAML 45 380 0 29 Mar 2021
Ensemble-in-One: Learning Ensemble within Random Gated Networks for Enhanced Adversarial Robustness Yi Cai Xuefei Ning Huazhong Yang Yu Wang AAML 27 4 0 27 Mar 2021
Combating Adversaries with Anti-Adversaries Motasem Alfarra Juan C. Pérez Ali K. Thabet Adel Bibi Philip Torr Guohao Li AAML 34 27 0 26 Mar 2021
MagDR: Mask-guided Detection and Reconstruction for Defending Deepfakes Zhikai Chen Lingxi Xie Shanmin Pang Yong He Bo Zhang AAML 36 32 0 26 Mar 2021
Boosting Adversarial Transferability through Enhanced Momentum Xiaosen Wang Jiadong Lin Han Hu Jingdong Wang Kun He AAML 14 76 0 19 Mar 2021
WaveGuard: Understanding and Mitigating Audio Adversarial Examples Shehzeen Samarah Hussain Paarth Neekhara Shlomo Dubnov Julian McAuley F. Koushanfar AAML 33 71 0 04 Mar 2021
Towards Adversarial-Resilient Deep Neural Networks for False Data Injection Attack Detection in Power Grids Jiangnan Li Yingyuan Yang Jinyuan Stella Sun K. Tomsovic Hairong Qi AAML 44 14 0 17 Feb 2021
Low Curvature Activations Reduce Overfitting in Adversarial Training Vasu Singla Sahil Singla David Jacobs S. Feizi AAML 43 45 0 15 Feb 2021
Resilient Machine Learning for Networked Cyber Physical Systems: A Survey for Machine Learning Security to Securing Machine Learning for CPS Felix O. Olowononi D. Rawat Chunmei Liu 38 134 0 14 Feb 2021
Mixed Nash Equilibria in the Adversarial Examples Game Laurent Meunier M. Scetbon Rafael Pinot Jamal Atif Y. Chevaleyre AAML 25 29 0 13 Feb 2021
"What's in the box?!": Deflecting Adversarial Attacks by Randomly Deploying Adversarially-Disjoint Models Sahar Abdelnabi Mario Fritz AAML 32 7 0 09 Feb 2021
Detecting Adversarial Examples by Input Transformations, Defense Perturbations, and Voting F. Nesti Alessandro Biondi Giorgio Buttazzo AAML 15 39 0 27 Jan 2021
Generalizing Adversarial Examples by AdaBelief Optimizer Yixiang Wang Jiqiang Liu Xiaolin Chang AAML 22 1 0 25 Jan 2021
A Comprehensive Evaluation Framework for Deep Model Robustness Jun Guo Wei Bao Jiakai Wang Yuqing Ma Xing Gao Gang Xiao Aishan Liu Zehao Zhao Xianglong Liu Wenjun Wu AAML ELM 38 55 0 24 Jan 2021
DiPSeN: Differentially Private Self-normalizing Neural Networks For Adversarial Robustness in Federated Learning Olakunle Ibitoye M. O. Shafiq Ashraf Matrawy FedML 28 18 0 08 Jan 2021
Local Competition and Stochasticity for Adversarial Robustness in Deep Learning Konstantinos P. Panousis S. Chatzis Antonios Alexos Sergios Theodoridis BDL AAML OOD 61 19 0 04 Jan 2021
Improving Adversarial Robustness via Probabilistically Compact Loss with Logit Constraints X. Li Xiangrui Li Deng Pan D. Zhu AAML 21 17 0 14 Dec 2020
Guided Adversarial Attack for Evaluating and Enhancing Adversarial Defenses Gaurang Sriramanan Sravanti Addepalli Arya Baburaj R. Venkatesh Babu AAML 28 92 0 30 Nov 2020
Exposing the Robustness and Vulnerability of Hybrid 8T-6T SRAM Memory Architectures to Adversarial Attacks in Deep Neural Networks Abhishek Moitra Priyadarshini Panda AAML 32 2 0 26 Nov 2020
Learnable Boundary Guided Adversarial Training Jiequan Cui Shu Liu Liwei Wang Jiaya Jia OOD AAML 30 124 0 23 Nov 2020
Almost Tight L0-norm Certified Robustness of Top-k Predictions against Adversarial Perturbations Jinyuan Jia Binghui Wang Xiaoyu Cao Hongbin Liu Neil Zhenqiang Gong 21 24 0 15 Nov 2020
The Vulnerability of the Neural Networks Against Adversarial Examples in Deep Learning Algorithms Rui Zhao AAML 34 1 0 02 Nov 2020
Towards Robust Neural Networks via Orthogonal Diversity Kun Fang Qinghua Tao Yingwen Wu Tao Li Jia Cai Feipeng Cai Xiaolin Huang Jie Yang AAML 41 8 0 23 Oct 2020
A Hamiltonian Monte Carlo Method for Probabilistic Adversarial Attack and Learning Hongjun Wang Guanbin Li Xiaobai Liu Liang Lin GAN AAML 21 22 0 15 Oct 2020
Higher-Order Certification for Randomized Smoothing Jeet Mohapatra Ching-Yun Ko Tsui-Wei Weng Pin-Yu Chen Sijia Liu Luca Daniel AAML 23 44 0 13 Oct 2020
Block-wise Image Transformation with Secret Key for Adversarially Robust Defense Maungmaung Aprilpyone Hitoshi Kiya 29 57 0 02 Oct 2020
Adversarial Training with Stochastic Weight Average Joong-won Hwang Youngwan Lee Sungchan Oh Yuseok Bae OOD AAML 31 11 0 21 Sep 2020
Defending Against Multiple and Unforeseen Adversarial Videos Shao-Yuan Lo Vishal M. Patel AAML 31 23 0 11 Sep 2020
Adversarial Machine Learning in Image Classification: A Survey Towards the Defender's Perspective G. R. Machado Eugênio Silva R. Goldschmidt AAML 33 157 0 08 Sep 2020
On the Intrinsic Robustness of NVM Crossbars Against Adversarial Attacks Deboleena Roy I. Chakraborty Timur Ibrayev Kaushik Roy AAML 19 4 0 27 Aug 2020
Rethinking Non-idealities in Memristive Crossbars for Adversarial Robustness in Neural Networks Abhiroop Bhattacharjee Priyadarshini Panda AAML 40 19 0 25 Aug 2020
Adversarial Examples on Object Recognition: A Comprehensive Survey A. Serban E. Poll Joost Visser AAML 32 73 0 07 Aug 2020
RANDOM MASK: Towards Robust Convolutional Neural Networks Tiange Luo Tianle Cai Mengxiao Zhang Siyu Chen Liwei Wang AAML OOD 24 17 0 27 Jul 2020