v1v2v3v4 (latest)

Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples

1 February 2018

Papers citing "Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples"

50 / 1,929 papers shown

Title
Label Noise in Adversarial Training: A Novel Perspective to Study Robust Overfitting Chengyu Dong Liyuan Liu Jingbo Shang NoLa AAML 119 20 0 07 Oct 2021
Improving Adversarial Robustness for Free with Snapshot Ensemble Yihao Wang AAML UQCV 38 1 0 07 Oct 2021
HIRE-SNN: Harnessing the Inherent Robustness of Energy-Efficient Deep Spiking Neural Networks by Training with Crafted Input Noise Souvik Kundu Massoud Pedram Peter A. Beerel AAML 88 76 0 06 Oct 2021
Calibrated Adversarial Training Tianjin Huang Vlado Menkovski Yulong Pei Mykola Pechenizkiy AAML 119 3 0 01 Oct 2021
Mitigating Black-Box Adversarial Attacks via Output Noise Perturbation Manjushree B. Aithal Xiaohua Li AAML 101 6 0 30 Sep 2021
Back in Black: A Comparative Evaluation of Recent State-Of-The-Art Black-Box Attacks Kaleel Mahmood Rigel Mahmood Ethan Rathbun Marten van Dijk AAML 76 22 0 29 Sep 2021
Unsolved Problems in ML Safety Dan Hendrycks Nicholas Carlini John Schulman Jacob Steinhardt 293 294 0 28 Sep 2021
MUTEN: Boosting Gradient-Based Adversarial Attacks via Mutant-Based Ensembles Yuejun Guo Qiang Hu Maxime Cordy Michail Papadakis Yves Le Traon AAML 50 3 0 27 Sep 2021
Two Souls in an Adversarial Image: Towards Universal Adversarial Example Detection using Multi-view Inconsistency Sohaib Kiani S. Awan Chao Lan Fengjun Li Bo Luo GAN AAML 44 7 0 25 Sep 2021
Auditing AI models for Verified Deployment under Semantic Specifications Homanga Bharadhwaj De-An Huang Chaowei Xiao Anima Anandkumar Animesh Garg MLAU 100 6 0 25 Sep 2021
Adversarial Transfer Attacks With Unknown Data and Class Overlap Luke E. Richards A. Nguyen Ryan Capps Steven D. Forsythe Cynthia Matuszek Edward Raff AAML 92 7 0 23 Sep 2021
CC-Cert: A Probabilistic Approach to Certify General Robustness of Neural Networks Mikhail Aleksandrovich Pautov Nurislam Tursynbek Marina Munkhoeva Nikita Muravev Aleksandr Petiushko Ivan Oseledets AAML 95 16 0 22 Sep 2021
Modeling Adversarial Noise for Adversarial Training Dawei Zhou Nannan Wang Bo Han Tongliang Liu AAML 95 16 0 21 Sep 2021
On the Noise Stability and Robustness of Adversarially Trained Networks on NVM Crossbars Chun Tao Deboleena Roy I. Chakraborty Kaushik Roy AAML 81 2 0 19 Sep 2021
Simple Post-Training Robustness Using Test Time Augmentations and Random Forest Gilad Cohen Raja Giryes AAML 71 4 0 16 Sep 2021
2-in-1 Accelerator: Enabling Random Precision Switch for Winning Both Adversarial Robustness and Efficiency Yonggan Fu Yang Zhao Qixuan Yu Chaojian Li Yingyan Lin AAML 170 14 0 11 Sep 2021
RobustART: Benchmarking Robustness on Architecture Design and Training Techniques Shiyu Tang Ruihao Gong Yan Wang Aishan Liu Jiakai Wang ... Xianglong Liu Basel Alomair Alan Yuille Philip Torr Dacheng Tao VLM AAML 102 108 0 11 Sep 2021
Energy Attack: On Transferring Adversarial Examples Ruoxi Shi Borui Yang Yangzhou Jiang Chenglong Zhao Bingbing Ni AAML 33 2 0 09 Sep 2021
Robustness and Generalization via Generative Adversarial Training Omid Poursaeed Tianxing Jiang Harry Yang Serge Belongie SerNam Lim OOD AAML 68 26 0 06 Sep 2021
Utilizing Adversarial Targeted Attacks to Boost Adversarial Robustness Uriya Pesso Koby Bibas M. Feder AAML 32 2 0 04 Sep 2021
SEC4SR: A Security Analysis Platform for Speaker Recognition Guangke Chen Zhe Zhao Fu Song Sen Chen Lingling Fan Yang Liu AAML 80 12 0 04 Sep 2021
A Synergetic Attack against Neural Network Classifiers combining Backdoor and Adversarial Examples Guanxiong Liu Issa M. Khalil Abdallah Khreishah Nhathai Phan SILM AAML 44 15 0 03 Sep 2021
Regional Adversarial Training for Better Robust Generalization Chuanbiao Song Yanbo Fan Yichen Yang Baoyuan Wu Yiming Li Zhifeng Li Kun He AAML OOD 131 8 0 02 Sep 2021
Morphence: Moving Target Defense Against Adversarial Examples Abderrahmen Amich Birhanu Eshete AAML 83 24 0 31 Aug 2021
Recent advances for quantum classifiers Weikang Li D. Deng AAML 94 87 0 30 Aug 2021
Sample Efficient Detection and Classification of Adversarial Attacks via Self-Supervised Embeddings Mazda Moayeri Soheil Feizi AAML 42 19 0 30 Aug 2021
Investigating Vulnerabilities of Deep Neural Policies Ezgi Korkmaz AAML 55 35 0 30 Aug 2021
DropAttack: A Masked Weight Adversarial Training Method to Improve Generalization of Neural Networks Shiwen Ni Jiawen Li Hung-Yu kao AAML 61 4 0 29 Aug 2021
Disrupting Adversarial Transferability in Deep Neural Networks Christopher Wiedeman Ge Wang AAML 96 7 0 27 Aug 2021
Understanding the Logit Distributions of Adversarially-Trained Deep Neural Networks Landan Seguin A. Ndirango Neeli Mishra SueYeon Chung Tyler Lee OOD 55 2 0 26 Aug 2021
A Hierarchical Assessment of Adversarial Severity Guillaume Jeanneret Juan Pérez Pablo Arbeláez AAML 56 2 0 26 Aug 2021
Certifiers Make Neural Networks Vulnerable to Availability Attacks Tobias Lorenz Marta Kwiatkowska Mario Fritz AAML SILM 71 3 0 25 Aug 2021
Adversarially Robust One-class Novelty Detection Shao-Yuan Lo Poojan Oza Vishal M. Patel AAML 71 32 0 25 Aug 2021
Bridged Adversarial Training Hoki Kim Woojin Lee Sungyoon Lee Jaewook Lee AAML GAN 70 9 0 25 Aug 2021
Kryptonite: An Adversarial Attack Using Regional Focus Yogesh Kulkarni Krisha Bhambani AAML 70 3 0 23 Aug 2021
PatchCleanser: Certifiably Robust Defense against Adversarial Patches for Any Image Classifier Chong Xiang Saeed Mahloujifar Prateek Mittal VLM AAML 103 78 0 20 Aug 2021
AdvDrop: Adversarial Attack to DNNs by Dropping Information Ranjie Duan YueFeng Chen Dantong Niu Yun Yang •. A. K. Qin Yuan He AAML 82 92 0 20 Aug 2021
Exploiting Multi-Object Relationships for Detecting Adversarial Attacks in Complex Scenes Mingjun Yin Shasha Li Zikui Cai Chengyu Song M. Salman Asif Amit K. Roy-Chowdhury S. Krishnamurthy AAML 73 20 0 19 Aug 2021
Revisiting Adversarial Robustness Distillation: Robust Soft Labels Make Student Better Bojia Zi Shihao Zhao Xingjun Ma Yu-Gang Jiang AAML 72 102 0 18 Aug 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 69 15 0 13 Aug 2021
Jujutsu: A Two-stage Defense against Adversarial Patch Attacks on Deep Neural Networks Zitao Chen Pritam Dash Karthik Pattabiraman AAML 85 18 0 11 Aug 2021
On Procedural Adversarial Noise Attack And Defense Jun Yan Xiaoyang Deng Huilin Yin Wancheng Ge AAML 58 2 0 10 Aug 2021
Neural Network Repair with Reachability Analysis Xiaodong Yang Tomochika Yamaguchi Hoang-Dung Tran Bardh Hoxha Taylor T. Johnson Danil Prokhorov AAML 62 30 0 09 Aug 2021
The Devil is in the GAN: Backdoor Attacks and Defenses in Deep Generative Models Ambrish Rawat Killian Levacher M. Sinn AAML 105 14 0 03 Aug 2021
AdvRush: Searching for Adversarially Robust Neural Architectures J. Mok Byunggook Na Hyeokjun Choe Sungroh Yoon OOD AAML 85 45 0 03 Aug 2021
Advances in adversarial attacks and defenses in computer vision: A survey Naveed Akhtar Ajmal Mian Navid Kardan M. Shah AAML 165 242 0 01 Aug 2021
Towards Adversarially Robust and Domain Generalizable Stereo Matching by Rethinking DNN Feature Backbones Ke Cheng Christopher Healey Tianfu Wu AAML OOD 51 2 0 31 Jul 2021
Delving into Deep Image Prior for Adversarial Defense: A Novel Reconstruction-based Defense Framework Li Ding Yongwei Wang Xin Ding Kaiwen Yuan Ping Wang Hua Huang Z. J. Wang AAML 52 7 0 31 Jul 2021
Enhancing Adversarial Robustness via Test-time Transformation Ensembling Juan C. Pérez Motasem Alfarra Guillaume Jeanneret Laura Rueda Ali K. Thabet Guohao Li Pablo Arbelaez 71 26 0 29 Jul 2021
Imbalanced Adversarial Training with Reweighting Wentao Wang Han Xu Xiaorui Liu Yaxin Li B. Thuraisingham Jiliang Tang 84 16 0 28 Jul 2021