Defense Against Adversarial Attacks Using Feature Scattering-based Adversarial Training

24 July 2019

Papers citing "Defense Against Adversarial Attacks Using Feature Scattering-based Adversarial Training"

38 / 38 papers shown

Title
A Study on Adversarial Robustness of Discriminative Prototypical Learning Ramin Zarei-Sabzevar Hamed Mohammadzadeh Tahmineh Tavakoli Ahad Harati AAML 16 0 0 03 Apr 2025
Weakly Supervised Contrastive Adversarial Training for Learning Robust Features from Semi-supervised Data Lilin Zhang Chengpei Wu Ning Yang 34 0 0 14 Mar 2025
A Survey of Adversarial Defenses in Vision-based Systems: Categorization, Methods and Challenges Nandish Chattopadhyay Abdul Basit B. Ouni Muhammad Shafique AAML 28 0 0 01 Mar 2025
Adversarial Training: A Survey Mengnan Zhao Lihe Zhang Jingwen Ye Huchuan Lu Baocai Yin Xinchao Wang AAML 28 0 0 19 Oct 2024
FuRL: Visual-Language Models as Fuzzy Rewards for Reinforcement Learning Yuwei Fu Haichao Zhang Di Wu Wei-ping Xu Benoit Boulet VLM 24 12 0 02 Jun 2024
Improving deep learning with prior knowledge and cognitive models: A survey on enhancing explainability, adversarial robustness and zero-shot learning F. Mumuni A. Mumuni AAML 27 5 0 11 Mar 2024
SoK: Analyzing Adversarial Examples: A Framework to Study Adversary Knowledge L. Fenaux Florian Kerschbaum AAML 29 0 0 22 Feb 2024
A Random Ensemble of Encrypted Vision Transformers for Adversarially Robust Defense Ryota Iijima Sayaka Shiota Hitoshi Kiya 28 6 0 11 Feb 2024
Mixing Classifiers to Alleviate the Accuracy-Robustness Trade-Off Yatong Bai Brendon G. Anderson Somayeh Sojoudi AAML 22 2 0 26 Nov 2023
IRAD: Implicit Representation-driven Image Resampling against Adversarial Attacks Yue Cao Tianlin Li Xiaofeng Cao Ivor Tsang Yang Liu Qing-Wu Guo AAML 21 2 0 18 Oct 2023
Robustness-enhanced Uplift Modeling with Adversarial Feature Desensitization Zexu Sun Bowei He Ming Ma Jiakai Tang Yuchen Wang Chen-li Ma Dugang Liu 21 4 0 07 Oct 2023
Splitting the Difference on Adversarial Training Matan Levi A. Kontorovich 32 4 0 03 Oct 2023
How Deep Learning Sees the World: A Survey on Adversarial Attacks & Defenses Joana Cabral Costa Tiago Roxo Hugo Manuel Proença Pedro R. M. Inácio AAML 30 48 0 18 May 2023
Randomized Adversarial Training via Taylor Expansion Gao Jin Xinping Yi Dengyu Wu Ronghui Mu Xiaowei Huang AAML 31 34 0 19 Mar 2023
Improving the Accuracy-Robustness Trade-Off of Classifiers via Adaptive Smoothing Yatong Bai Brendon G. Anderson Aerin Kim Somayeh Sojoudi AAML 26 18 0 29 Jan 2023
Increasing Confidence in Adversarial Robustness Evaluations Roland S. Zimmermann Wieland Brendel Florian Tramèr Nicholas Carlini AAML 36 16 0 28 Jun 2022
How Does Frequency Bias Affect the Robustness of Neural Image Classifiers against Common Corruption and Adversarial Perturbations? Alvin Chan Yew-Soon Ong Clement Tan AAML 22 13 0 09 May 2022
CE-based white-box adversarial attacks will not work using super-fitting Youhuan Yang Lei Sun Leyu Dai Song Guo Xiuqing Mao Xiaoqin Wang Bayi Xu AAML 24 0 0 04 May 2022
A Survey of Robust Adversarial Training in Pattern Recognition: Fundamental, Theory, and Methodologies Zhuang Qian Kaizhu Huang Qiufeng Wang Xu-Yao Zhang OOD AAML ObjD 47 71 0 26 Mar 2022
Enhancing Adversarial Training with Second-Order Statistics of Weights Gao Jin Xinping Yi Wei Huang S. Schewe Xiaowei Huang AAML 10 46 0 11 Mar 2022
Frequency-driven Imperceptible Adversarial Attack on Semantic Similarity Cheng Luo Qinliang Lin Weicheng Xie Bizhu Wu Jinheng Xie Linlin Shen AAML 17 100 0 10 Mar 2022
Global-Local Regularization Via Distributional Robustness Hoang Phan Trung Le Trung-Nghia Phung Tu Bui Nhat Ho Dinh Q. Phung OOD 9 12 0 01 Mar 2022
A Unified Wasserstein Distributional Robustness Framework for Adversarial Training Tu Bui Trung Le Quan Hung Tran He Zhao Dinh Q. Phung AAML OOD 23 42 0 27 Feb 2022
An Overview of Compressible and Learnable Image Transformation with Secret Key and Its Applications Hitoshi Kiya AprilPyone Maungmaung Yuma Kinoshita Shoko Imaizumi Sayaka Shiota 12 58 0 26 Jan 2022
Human Imperceptible Attacks and Applications to Improve Fairness Xinru Hua Huanzhong Xu Jose H. Blanchet V. Nguyen AAML 11 3 0 30 Nov 2021
AGKD-BML: Defense Against Adversarial Attack by Attention Guided Knowledge Distillation and Bi-directional Metric Learning Hong Wang Yuefan Deng Shinjae Yoo Haibin Ling Yuewei Lin AAML 17 15 0 13 Aug 2021
Adversarial Reinforced Instruction Attacker for Robust Vision-Language Navigation Bingqian Lin Yi Zhu Yanxin Long Xiaodan Liang QiXiang Ye Liang Lin AAML 31 16 0 23 Jul 2021
Localized Uncertainty Attacks Ousmane Amadou Dia Theofanis Karaletsos C. Hazirbas Cristian Canton Ferrer I. Kabul E. Meijer AAML 19 2 0 17 Jun 2021
Quality Assurance Challenges for Machine Learning Software Applications During Software Development Life Cycle Phases Md. Abdullah Al Alamin Gias Uddin 16 11 0 03 May 2021
LAFEAT: Piercing Through Adversarial Defenses with Latent Features Yunrui Yu Xitong Gao Chengzhong Xu AAML FedML 17 44 0 19 Apr 2021
Mitigating Adversarial Attack for Compute-in-Memory Accelerator Utilizing On-chip Finetune Shanshi Huang Hongwu Jiang Shimeng Yu AAML 26 3 0 13 Apr 2021
Robustness of on-device Models: Adversarial Attack to Deep Learning Models on Android Apps Yujin Huang Han Hu Chunyang Chen AAML FedML 72 33 0 12 Jan 2021
Uncovering the Limits of Adversarial Training against Norm-Bounded Adversarial Examples Sven Gowal Chongli Qin J. Uesato Timothy A. Mann Pushmeet Kohli AAML 17 323 0 07 Oct 2020
Simulating Unknown Target Models for Query-Efficient Black-box Attacks Chen Ma L. Chen Junhai Yong MLAU OOD 31 17 0 02 Sep 2020
Stylized Adversarial Defense Muzammal Naseer Salman Khan Munawar Hayat F. Khan Fatih Porikli GAN AAML 20 16 0 29 Jul 2020
Large-Scale Adversarial Training for Vision-and-Language Representation Learning Zhe Gan Yen-Chun Chen Linjie Li Chen Zhu Yu Cheng Jingjing Liu ObjD VLM 24 487 0 11 Jun 2020
Learn2Perturb: an End-to-end Feature Perturbation Learning to Improve Adversarial Robustness Ahmadreza Jeddi M. Shafiee Michelle Karg C. Scharfenberger A. Wong OOD AAML 48 63 0 02 Mar 2020
Adversarial Machine Learning at Scale Alexey Kurakin Ian Goodfellow Samy Bengio AAML 256 3,108 0 04 Nov 2016