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Adversarial examples in the physical world

8 July 2016

Papers citing "Adversarial examples in the physical world"

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Title
Exploring the Vulnerability of Deep Neural Networks: A Study of Parameter Corruption Xu Sun Zhiyuan Zhang Xuancheng Ren Ruixuan Luo Liangyou Li 68 40 0 10 Jun 2020
GAP++: Learning to generate target-conditioned adversarial examples Xiaofeng Mao YueFeng Chen Yuhong Li Yuan He Hui Xue AAML 78 8 0 09 Jun 2020
Calibrated neighborhood aware confidence measure for deep metric learning Maryna Karpusha Sunghee Yun István Fehérvári UQCV FedML 126 2 0 08 Jun 2020
A Self-supervised Approach for Adversarial Robustness Muzammal Naseer Salman Khan Munawar Hayat Fahad Shahbaz Khan Fatih Porikli AAML 93 262 0 08 Jun 2020
BERT Loses Patience: Fast and Robust Inference with Early Exit Wangchunshu Zhou Canwen Xu Tao Ge Julian McAuley Ke Xu Furu Wei 79 344 0 07 Jun 2020
Lipschitz Bounds and Provably Robust Training by Laplacian Smoothing Vishaal Krishnan Abed AlRahman Al Makdah Fabio Pasqualetti OOD AAML 78 23 0 05 Jun 2020
Robust Face Verification via Disentangled Representations Marius Arvinte Ahmed H. Tewfik S. Vishwanath CVBM 43 1 0 05 Jun 2020
mFI-PSO: A Flexible and Effective Method in Adversarial Image Generation for Deep Neural Networks Hai Shu Ronghua Shi Qiran Jia Hongtu Zhu Ziqi Chen AAML 42 2 0 05 Jun 2020
Pick-Object-Attack: Type-Specific Adversarial Attack for Object Detection Omid Mohamad Nezami Akshay Chaturvedi Mark Dras Utpal Garain AAML ObjD 61 19 0 05 Jun 2020
Adversarial Item Promotion: Vulnerabilities at the Core of Top-N Recommenders that Use Images to Address Cold Start Zhuoran Liu Martha Larson DiffM 65 28 0 02 Jun 2020
Perturbation Analysis of Gradient-based Adversarial Attacks Utku Ozbulak Manvel Gasparyan W. D. Neve Arnout Van Messem AAML 34 7 0 02 Jun 2020
A Multi-modal Neural Embeddings Approach for Detecting Mobile Counterfeit Apps: A Case Study on Google Play Store Naveen Karunanayake Jathushan Rajasegaran Ashanie Gunathillake Suranga Seneviratne Guillaume Jourjon 131 15 0 02 Jun 2020
Exploring the role of Input and Output Layers of a Deep Neural Network in Adversarial Defense Jay N. Paranjape R. Dubey Vijendran V. Gopalan AAML 49 2 0 02 Jun 2020
Rethinking Empirical Evaluation of Adversarial Robustness Using First-Order Attack Methods Kyungmi Lee A. Chandrakasan ELM AAML 69 3 0 01 Jun 2020
Adversarial Attacks on Reinforcement Learning based Energy Management Systems of Extended Range Electric Delivery Vehicles Pengyue Wang Yuante Li Shashi Shekhar W. Northrop AAML 57 8 0 01 Jun 2020
Second-Order Provable Defenses against Adversarial Attacks Sahil Singla Soheil Feizi AAML 74 60 0 01 Jun 2020
Exploring Model Robustness with Adaptive Networks and Improved Adversarial Training Zheng Xu Ali Shafahi Tom Goldstein AAML 51 2 0 30 May 2020
Monocular Depth Estimators: Vulnerabilities and Attacks Alwyn Mathew Aditya Patra Jimson Mathew AAML MDE 42 9 0 28 May 2020
Deceptive Deletions for Protecting Withdrawn Posts on Social Platforms Mohsen Minaei S Chandra Mouli Mainack Mondal Bruno Ribeiro Aniket Kate 39 9 0 28 May 2020
Mitigating Advanced Adversarial Attacks with More Advanced Gradient Obfuscation Techniques Han Qiu Yi Zeng Qinkai Zheng Tianwei Zhang Meikang Qiu G. Memmi AAML 69 14 0 27 May 2020
Enhancing Resilience of Deep Learning Networks by Means of Transferable Adversaries M. Seiler Heike Trautmann P. Kerschke AAML 24 0 0 27 May 2020
Effects of Forward Error Correction on Communications Aware Evasion Attacks Matthew DelVecchio Bryse Flowers William C. Headley AAML 34 7 0 27 May 2020
Adaptive Adversarial Logits Pairing Shangxi Wu Jitao Sang Kaiyan Xu Guanhua Zheng Changsheng Xu AAML 31 3 0 25 May 2020
Inaudible Adversarial Perturbations for Targeted Attack in Speaker Recognition Qing Wang Pengcheng Guo Lei Xie AAML 82 57 0 21 May 2020
Model-Based Robust Deep Learning: Generalizing to Natural, Out-of-Distribution Data Alexander Robey Hamed Hassani George J. Pappas OOD 107 43 0 20 May 2020
Data Consistent CT Reconstruction from Insufficient Data with Learned Prior Images Yixing Huang Alexander Preuhs M. Manhart G. Lauritsch Andreas Maier MedIm 158 5 0 20 May 2020
Identifying Statistical Bias in Dataset Replication Logan Engstrom Andrew Ilyas Shibani Santurkar Dimitris Tsipras Jacob Steinhardt Aleksander Madry 84 51 0 19 May 2020
SINVAD: Search-based Image Space Navigation for DNN Image Classifier Test Input Generation Sungmin Kang R. Feldt S. Yoo AAML 92 32 0 19 May 2020
Synthesizing Unrestricted False Positive Adversarial Objects Using Generative Models Martin Kotuliak Sandro Schönborn Andrei Dan GAN AAML 36 1 0 19 May 2020
Bias-based Universal Adversarial Patch Attack for Automatic Check-out Aishan Liu Jiakai Wang Xianglong Liu Bowen Cao Chongzhi Zhang Hang Yu AAML 60 5 0 19 May 2020
On Intrinsic Dataset Properties for Adversarial Machine Learning J. Z. Pan Nicholas Zufelt AAML 40 1 0 19 May 2020
Increasing-Margin Adversarial (IMA) Training to Improve Adversarial Robustness of Neural Networks Linhai Ma Liang Liang AAML 143 19 0 19 May 2020
Universalization of any adversarial attack using very few test examples Sandesh Kamath Amit Deshpande K. Subrahmanyam Vineeth N. Balasubramanian FedML AAML 38 1 0 18 May 2020
Deep Architecture Enhancing Robustness to Noise, Adversarial Attacks, and Cross-corpus Setting for Speech Emotion Recognition S. Latif R. Rana Sara Khalifa Raja Jurdak Björn W. Schuller 125 28 0 18 May 2020
Toward Adversarial Robustness by Diversity in an Ensemble of Specialized Deep Neural Networks Mahdieh Abbasi Arezoo Rajabi Christian Gagné R. Bobba AAML 39 15 0 17 May 2020
Universal Adversarial Perturbations: A Survey Ashutosh Chaubey Nikhil Agrawal Kavya Barnwal K. K. Guliani Pramod Mehta OOD AAML 110 47 0 16 May 2020
How to Make 5G Communications "Invisible": Adversarial Machine Learning for Wireless Privacy Brian Kim Y. Sagduyu Kemal Davaslioglu T. Erpek S. Ulukus AAML 51 29 0 15 May 2020
Initializing Perturbations in Multiple Directions for Fast Adversarial Training Xunguang Wang S. Xu E. Wang AAML 33 0 0 15 May 2020
Stealthy and Efficient Adversarial Attacks against Deep Reinforcement Learning Jianwen Sun Tianwei Zhang Xiaofei Xie Lei Ma Yan Zheng Kangjie Chen Yang Liu AAML 61 118 0 14 May 2020
Adversarial examples are useful too! Ali Borji SILM AAML 37 1 0 13 May 2020
Increased-confidence adversarial examples for deep learning counter-forensics Wenjie Li B. Tondi R. Ni Mauro Barni AAML 27 2 0 12 May 2020
Effective and Robust Detection of Adversarial Examples via Benford-Fourier Coefficients Chengcheng Ma Baoyuan Wu Shibiao Xu Yanbo Fan Yong Zhang Xiaopeng Zhang Zhifeng Li AAML 64 9 0 12 May 2020
Channel-Aware Adversarial Attacks Against Deep Learning-Based Wireless Signal Classifiers Brian Kim Y. Sagduyu Kemal Davaslioglu T. Erpek S. Ulukus AAML 89 119 0 11 May 2020
Class-Aware Domain Adaptation for Improving Adversarial Robustness Xianxu Hou Jingxin Liu Bolei Xu Xiaolong Wang Bozhi Liu Guoping Qiu OOD AAML 127 9 0 10 May 2020
Projection & Probability-Driven Black-Box Attack Jie Li Rongrong Ji Hong Liu Jianzhuang Liu Bineng Zhong Cheng Deng Q. Tian AAML 72 49 0 08 May 2020
Blind Backdoors in Deep Learning Models Eugene Bagdasaryan Vitaly Shmatikov AAML FedML SILM 163 311 0 08 May 2020
Towards Frequency-Based Explanation for Robust CNN Zifan Wang Yilin Yang Ankit Shrivastava Varun Rawal Zihao Ding AAML FAtt 57 49 0 06 May 2020
Enhancing Intrinsic Adversarial Robustness via Feature Pyramid Decoder Guanlin Li Shuya Ding Jun Luo Chang-rui Liu AAML 107 19 0 06 May 2020
A Causal View on Robustness of Neural Networks Cheng Zhang Kun Zhang Yingzhen Li CML OOD 109 85 0 03 May 2020
Explainable Deep Learning: A Field Guide for the Uninitiated Gabrielle Ras Ning Xie Marcel van Gerven Derek Doran AAML XAI 120 382 0 30 Apr 2020