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Towards Evaluating the Robustness of Neural Networks

16 August 2016

Papers citing "Towards Evaluating the Robustness of Neural Networks"

50 / 4,017 papers shown

Title
Deep Latent Defence Giulio Zizzo C. Hankin S. Maffeis K. Jones AAML 49 2 0 09 Oct 2019
SmoothFool: An Efficient Framework for Computing Smooth Adversarial Perturbations Ali Dabouei Sobhan Soleymani Fariborz Taherkhani J. Dawson Nasser M. Nasrabadi AAML 149 19 0 08 Oct 2019
Detecting AI Trojans Using Meta Neural Analysis Xiaojun Xu Qi Wang Huichen Li Nikita Borisov Carl A. Gunter Yue Liu 132 329 0 08 Oct 2019
Testing and verification of neural-network-based safety-critical control software: A systematic literature review Jin Zhang Jingyue Li 93 48 0 05 Oct 2019
BUZz: BUffer Zones for defending adversarial examples in image classification Kaleel Mahmood Phuong Ha Nguyen Lam M. Nguyen THANH VAN NGUYEN Marten van Dijk AAML 62 6 0 03 Oct 2019
Partial differential equation regularization for supervised machine learning Jillian R. Fisher 63 2 0 03 Oct 2019
Robust Risk Minimization for Statistical Learning Muhammad Osama Dave Zachariah Petre Stoica OOD 48 7 0 03 Oct 2019
Perturbations are not Enough: Generating Adversarial Examples with Spatial Distortions He Zhao Trung Le Paul Montague O. Vel Tamas Abraham Dinh Q. Phung AAML 67 8 0 03 Oct 2019
Analyzing and Improving Neural Networks by Generating Semantic Counterexamples through Differentiable Rendering Lakshya Jain Varun Chandrasekaran Uyeong Jang Wilson Wu Andrew Lee Andy Yan Steven Chen S. Jha Sanjit A. Seshia AAML 72 11 0 02 Oct 2019
An Efficient and Margin-Approaching Zero-Confidence Adversarial Attack Yang Zhang Shiyu Chang Mo Yu Kaizhi Qian AAML 29 2 0 01 Oct 2019
Deep Neural Rejection against Adversarial Examples Angelo Sotgiu Ambra Demontis Marco Melis Battista Biggio Giorgio Fumera Xiaoyi Feng Fabio Roli AAML 88 69 0 01 Oct 2019
Cross-Layer Strategic Ensemble Defense Against Adversarial Examples Wenqi Wei Ling Liu Margaret Loper Ka-Ho Chow Emre Gursoy Stacey Truex Yanzhao Wu AAML 52 12 0 01 Oct 2019
Synthesizing Action Sequences for Modifying Model Decisions Goutham Ramakrishnan Yun Chan Lee Aws Albarghouthi 127 33 0 30 Sep 2019
Black-box Adversarial Attacks with Bayesian Optimization Satya Narayan Shukla Anit Kumar Sahu Devin Willmott J. Zico Kolter AAML MLAU 73 31 0 30 Sep 2019
Min-Max Optimization without Gradients: Convergence and Applications to Adversarial ML Sijia Liu Songtao Lu Xiangyi Chen Yao Feng Kaidi Xu Abdullah Al-Dujaili Mingyi Hong Una-May Obelilly 94 26 0 30 Sep 2019
Impact of Low-bitwidth Quantization on the Adversarial Robustness for Embedded Neural Networks Rémi Bernhard Pierre-Alain Moëllic J. Dutertre AAML MQ 98 18 0 27 Sep 2019
Lower Bounds on Adversarial Robustness from Optimal Transport A. Bhagoji Daniel Cullina Prateek Mittal OOD OT AAML 74 94 0 26 Sep 2019
Adversarial Machine Learning Attack on Modulation Classification Muhammad Usama Muhammad Asim Junaid Qadir Ala I. Al-Fuqaha M. Imran AAML 32 15 0 26 Sep 2019
Sign-OPT: A Query-Efficient Hard-label Adversarial Attack Minhao Cheng Simranjit Singh Patrick H. Chen Pin-Yu Chen Sijia Liu Cho-Jui Hsieh AAML 252 224 0 24 Sep 2019
MemGuard: Defending against Black-Box Membership Inference Attacks via Adversarial Examples Jinyuan Jia Ahmed Salem Michael Backes Yang Zhang Neil Zhenqiang Gong 118 398 0 23 Sep 2019
FENCE: Feasible Evasion Attacks on Neural Networks in Constrained Environments Alesia Chernikova Alina Oprea AAML 121 40 0 23 Sep 2019
Robust Local Features for Improving the Generalization of Adversarial Training Chuanbiao Song Kun He Jiadong Lin Liwei Wang John E. Hopcroft OOD AAML 75 70 0 23 Sep 2019
Towards Interpreting Recurrent Neural Networks through Probabilistic Abstraction Guoliang Dong Jingyi Wang Jun Sun Yang Zhang Xinyu Wang Ting Dai J. Dong Xingen Wang FaML 58 3 0 22 Sep 2019
COPYCAT: Practical Adversarial Attacks on Visualization-Based Malware Detection Aminollah Khormali Ahmed A. Abusnaina Songqing Chen Daehun Nyang Aziz Mohaisen AAML 58 27 0 20 Sep 2019
Defending Against Physically Realizable Attacks on Image Classification Tong Wu Liang Tong Yevgeniy Vorobeychik AAML 84 127 0 20 Sep 2019
Toward Robust Image Classification Basemah Alshemali Alta Graham Jugal Kalita AAML 44 7 0 19 Sep 2019
Absum: Simple Regularization Method for Reducing Structural Sensitivity of Convolutional Neural Networks Sekitoshi Kanai Yasutoshi Ida Yasuhiro Fujiwara Masanori Yamada S. Adachi AAML 49 1 0 19 Sep 2019
Adversarial Attacks and Defenses in Images, Graphs and Text: A Review Han Xu Yao Ma Haochen Liu Debayan Deb Hui Liu Jiliang Tang Anil K. Jain AAML 90 680 0 17 Sep 2019
Defending against Machine Learning based Inference Attacks via Adversarial Examples: Opportunities and Challenges Jinyuan Jia Neil Zhenqiang Gong AAML SILM 87 17 0 17 Sep 2019
They Might NOT Be Giants: Crafting Black-Box Adversarial Examples with Fewer Queries Using Particle Swarm Optimization Rayan Mosli M. Wright Bo Yuan Yin Pan AAML 48 16 0 16 Sep 2019
Detecting Adversarial Samples Using Influence Functions and Nearest Neighbors Gilad Cohen Guillermo Sapiro Raja Giryes TDI 73 128 0 15 Sep 2019
An Empirical Study towards Characterizing Deep Learning Development and Deployment across Different Frameworks and Platforms Qianyu Guo Sen Chen Xiaofei Xie Lei Ma Q. Hu Hongtao Liu Yang Liu Jianjun Zhao Xiaohong Li 94 125 0 15 Sep 2019
An Empirical Investigation of Randomized Defenses against Adversarial Attacks Yannik Potdevin Dirk Nowotka Vijay Ganesh AAML 49 4 0 12 Sep 2019
Inspecting adversarial examples using the Fisher information Jörg Martin Clemens Elster AAML 50 15 0 12 Sep 2019
Sparse and Imperceivable Adversarial Attacks Francesco Croce Matthias Hein AAML 110 199 0 11 Sep 2019
PDA: Progressive Data Augmentation for General Robustness of Deep Neural Networks Hang Yu Aishan Liu Xianglong Liu Gen Li Ping Luo R. Cheng Jichen Yang Chongzhi Zhang AAML 85 10 0 11 Sep 2019
Effectiveness of Adversarial Examples and Defenses for Malware Classification Robert Podschwadt Hassan Takabi AAML 52 11 0 10 Sep 2019
Neural Belief Reasoner Haifeng Qian NAI BDL 26 1 0 10 Sep 2019
FDA: Feature Disruptive Attack Aditya Ganeshan S. VivekB. R. Venkatesh Babu AAML 124 105 0 10 Sep 2019
Adversarial Robustness Against the Union of Multiple Perturbation Models Pratyush Maini Eric Wong J. Zico Kolter OOD AAML 65 151 0 09 Sep 2019
When Explainability Meets Adversarial Learning: Detecting Adversarial Examples using SHAP Signatures Gil Fidel Ron Bitton A. Shabtai FAtt GAN 68 120 0 08 Sep 2019
Blackbox Attacks on Reinforcement Learning Agents Using Approximated Temporal Information Yiren Zhao Ilia Shumailov Han Cui Xitong Gao Robert D. Mullins Ross J. Anderson AAML 85 29 0 06 Sep 2019
Invisible Backdoor Attacks on Deep Neural Networks via Steganography and Regularization Shaofeng Li Minhui Xue Benjamin Zi Hao Zhao Haojin Zhu Dali Kaafar 85 60 0 06 Sep 2019
Are Adversarial Robustness and Common Perturbation Robustness Independent Attributes ? Alfred Laugros A. Caplier Matthieu Ospici AAML 56 40 0 04 Sep 2019
Metric Learning for Adversarial Robustness Chengzhi Mao Ziyuan Zhong Junfeng Yang Carl Vondrick Baishakhi Ray OOD 101 188 0 03 Sep 2019
Deep Neural Network Ensembles against Deception: Ensemble Diversity, Accuracy and Robustness Ling Liu Wenqi Wei Ka-Ho Chow Margaret Loper Emre Gursoy Stacey Truex Yanzhao Wu UQCV AAML FedML 77 60 0 29 Aug 2019
advPattern: Physical-World Attacks on Deep Person Re-Identification via Adversarially Transformable Patterns Peng Kuang Siyan Zheng Mengkai Song Qian Wang Alireza Rahimpour Hairong Qi AAML OOD 78 59 0 25 Aug 2019
Targeted Mismatch Adversarial Attack: Query with a Flower to Retrieve the Tower Giorgos Tolias Filip Radenovic Ondřej Chum AAML 77 71 0 24 Aug 2019
Improving Adversarial Robustness via Attention and Adversarial Logit Pairing Dou Goodman Xingjian Li Ji Liu Jun Huan Tao Wei AAML 45 7 0 23 Aug 2019
Saliency Methods for Explaining Adversarial Attacks Jindong Gu Volker Tresp FAtt AAML 71 30 0 22 Aug 2019