SafetyNet: Detecting and Rejecting Adversarial Examples Robustly

1 April 2017

Papers citing "SafetyNet: Detecting and Rejecting Adversarial Examples Robustly"

50 / 73 papers shown

Title
Understanding Deep Learning defenses Against Adversarial Examples Through Visualizations for Dynamic Risk Assessment Xabier Echeberria-Barrio Amaia Gil-Lerchundi Jon Egana-Zubia Raul Orduna Urrutia AAML 37 6 0 12 Feb 2024
Adversarial Examples Detection with Enhanced Image Difference Features based on Local Histogram Equalization Z. Yin Shaowei Zhu Han Su Jianteng Peng Wanli Lyu Bin Luo AAML 31 2 0 08 May 2023
Vertex-based reachability analysis for verifying ReLU deep neural networks João G. Zago E. Camponogara Eric A. Antonelo AAML 31 2 0 27 Jan 2023
TAD: Transfer Learning-based Multi-Adversarial Detection of Evasion Attacks against Network Intrusion Detection Systems Islam Debicha Richard Bauwens Thibault Debatty Jean-Michel Dricot Tayeb Kenaza Wim Mees AAML 24 40 0 27 Oct 2022
Secure and Trustworthy Artificial Intelligence-Extended Reality (AI-XR) for Metaverses Adnan Qayyum M. A. Butt Hassan Ali Muhammad Usman O. Halabi Ala I. Al-Fuqaha Q. Abbasi Muhammad Ali Imran Junaid Qadir 32 32 0 24 Oct 2022
Boosting Adversarial Robustness From The Perspective of Effective Margin Regularization Ziquan Liu Antoni B. Chan AAML 33 5 0 11 Oct 2022
Trace and Detect Adversarial Attacks on CNNs using Feature Response Maps Mohammadreza Amirian Friedhelm Schwenker Thilo Stadelmann AAML 27 16 0 24 Aug 2022
Threat Assessment in Machine Learning based Systems L. Tidjon Foutse Khomh 27 17 0 30 Jun 2022
Wavelet Regularization Benefits Adversarial Training Jun Yan Huilin Yin Xiaoyang Deng Zi-qin Zhao Wancheng Ge Hao Zhang Gerhard Rigoll AAML 19 2 0 08 Jun 2022
Attack-Agnostic Adversarial Detection Jiaxin Cheng Mohamed Hussein J. Billa Wael AbdAlmageed AAML 28 0 0 01 Jun 2022
A Tutorial on Adversarial Learning Attacks and Countermeasures Cato Pauling Michael Gimson Muhammed Qaid Ahmad Kida Basel Halak AAML 25 11 0 21 Feb 2022
Adversarial Attacks and Defense Methods for Power Quality Recognition Jiwei Tian Buhong Wang Jing Li Zhen Wang Mete Ozay AAML 26 0 0 11 Feb 2022
Fooling the Eyes of Autonomous Vehicles: Robust Physical Adversarial Examples Against Traffic Sign Recognition Systems Wei Jia Zhaojun Lu Haichun Zhang Zhenglin Liu Jie Wang Gang Qu AAML 16 51 0 17 Jan 2022
DeepAdversaries: Examining the Robustness of Deep Learning Models for Galaxy Morphology Classification A. Ćiprijanović Diana Kafkes Gregory F. Snyder F. Sánchez G. Perdue K. Pedro Brian D. Nord Sandeep Madireddy Stefan M. Wild AAML 42 15 0 28 Dec 2021
All You Need is RAW: Defending Against Adversarial Attacks with Camera Image Pipelines Yuxuan Zhang B. Dong Felix Heide AAML 26 8 0 16 Dec 2021
Explainable Deep Learning in Healthcare: A Methodological Survey from an Attribution View Di Jin Elena Sergeeva W. Weng Geeticka Chauhan Peter Szolovits OOD 47 55 0 05 Dec 2021
Medical Aegis: Robust adversarial protectors for medical images Qingsong Yao Zecheng He S. Kevin Zhou AAML MedIm 30 2 0 22 Nov 2021
Mitigating Black-Box Adversarial Attacks via Output Noise Perturbation Manjushree B. Aithal Xiaohua Li AAML 60 6 0 30 Sep 2021
SoK: Machine Learning Governance Varun Chandrasekaran Hengrui Jia Anvith Thudi Adelin Travers Mohammad Yaghini Nicolas Papernot 40 16 0 20 Sep 2021
Detecting Textual Adversarial Examples through Randomized Substitution and Vote Xiaosen Wang Yifeng Xiong Kun He AAML 27 11 0 13 Sep 2021
Optical Adversarial Attack Abhiram Gnanasambandam A. Sherman Stanley H. Chan AAML 35 65 0 13 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 32 15 0 13 Aug 2021
Inconspicuous Adversarial Patches for Fooling Image Recognition Systems on Mobile Devices Tao Bai Jinqi Luo Jun Zhao AAML 31 30 0 29 Jun 2021
We Can Always Catch You: Detecting Adversarial Patched Objects WITH or WITHOUT Signature Binxiu Liang Jiachun Li Jianjun Huang AAML 33 12 0 09 Jun 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
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
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 38 133 0 14 Feb 2021
Generating Adversarial yet Inconspicuous Patches with a Single Image Jinqi Luo Tao Bai Jun Zhao AAML 27 6 0 21 Sep 2020
The Intriguing Relation Between Counterfactual Explanations and Adversarial Examples Timo Freiesleben GAN 43 62 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
Defending Adversarial Examples via DNN Bottleneck Reinforcement Wenqing Liu Miaojing Shi Teddy Furon Li Li AAML 26 8 0 12 Aug 2020
Adversarial Examples on Object Recognition: A Comprehensive Survey A. Serban E. Poll Joost Visser AAML 29 73 0 07 Aug 2020
Cassandra: Detecting Trojaned Networks from Adversarial Perturbations Xiaoyu Zhang Ajmal Mian Rohit Gupta Nazanin Rahnavard M. Shah AAML 34 26 0 28 Jul 2020
AdvFoolGen: Creating Persistent Troubles for Deep Classifiers Yuzhen Ding Nupur Thakur Baoxin Li AAML 24 3 0 20 Jul 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 21 2 0 02 Jun 2020
Few-Shot Open-Set Recognition using Meta-Learning Bo Liu Hao Kang Haoxiang Li G. Hua Nuno Vasconcelos BDL EDL 28 89 0 27 May 2020
Adversarial Attacks and Defenses: An Interpretation Perspective Ninghao Liu Mengnan Du Ruocheng Guo Huan Liu Xia Hu AAML 31 8 0 23 Apr 2020
Towards Robust Classification with Image Quality Assessment Yeli Feng Yiyu Cai 19 0 0 14 Apr 2020
Anomalous Example Detection in Deep Learning: A Survey Saikiran Bulusu B. Kailkhura Bo-wen Li P. Varshney D. Song AAML 28 47 0 16 Mar 2020
Toward Adversarial Robustness via Semi-supervised Robust Training Yiming Li Baoyuan Wu Yan Feng Yanbo Fan Yong Jiang Zhifeng Li Shutao Xia AAML 87 13 0 16 Mar 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 72 63 0 02 Mar 2020
Utilizing Network Properties to Detect Erroneous Inputs Matt Gorbett Nathaniel Blanchard AAML 23 6 0 28 Feb 2020
Adversarial Ranking Attack and Defense Mo Zhou Zhenxing Niu Le Wang Qilin Zhang G. Hua 36 38 0 26 Feb 2020
Gödel's Sentence Is An Adversarial Example But Unsolvable Xiaodong Qi Lansheng Han AAML 30 0 0 25 Feb 2020
Attacking Optical Character Recognition (OCR) Systems with Adversarial Watermarks Lu Chen Wenyuan Xu AAML 24 21 0 08 Feb 2020
Minimax Defense against Gradient-based Adversarial Attacks Blerta Lindqvist R. Izmailov AAML 19 0 0 04 Feb 2020
Deep Neural Rejection against Adversarial Examples Angelo Sotgiu Ambra Demontis Marco Melis Battista Biggio Giorgio Fumera Xiaoyi Feng Fabio Roli AAML 22 68 0 01 Oct 2019
Impact of Low-bitwidth Quantization on the Adversarial Robustness for Embedded Neural Networks Rémi Bernhard Pierre-Alain Moëllic J. Dutertre AAML MQ 24 18 0 27 Sep 2019
Securing Connected & Autonomous Vehicles: Challenges Posed by Adversarial Machine Learning and The Way Forward A. Qayyum Muhammad Usama Junaid Qadir Ala I. Al-Fuqaha AAML 27 187 0 29 May 2019
ROSA: Robust Salient Object Detection against Adversarial Attacks Haofeng Li Guanbin Li Yizhou Yu AAML 13 28 0 09 May 2019