Towards Evaluating the Robustness of Neural Networks

16 August 2016

Papers citing "Towards Evaluating the Robustness of Neural Networks"

50 / 1,609 papers shown

Title
Detecting AI Trojans Using Meta Neural Analysis Xiaojun Xu Qi Wang Huichen Li Nikita Borisov Carl A. Gunter Bo-wen Li 31 321 0 08 Oct 2019
Partial differential equation regularization for supervised machine learning Jillian R. Fisher 27 2 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 28 8 0 03 Oct 2019
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
Black-box Adversarial Attacks with Bayesian Optimization Satya Narayan Shukla Anit Kumar Sahu Devin Willmott J. Zico Kolter AAML MLAU 14 30 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 24 18 0 27 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 134 219 0 24 Sep 2019
COPYCAT: Practical Adversarial Attacks on Visualization-Based Malware Detection Aminollah Khormali Ahmed A. Abusnaina Songqing Chen Daehun Nyang Aziz Mohaisen AAML 34 28 0 20 Sep 2019
Defending Against Physically Realizable Attacks on Image Classification Tong Wu Liang Tong Yevgeniy Vorobeychik AAML 25 125 0 20 Sep 2019
Toward Robust Image Classification Basemah Alshemali Alta Graham Jugal Kalita AAML 40 6 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 23 1 0 19 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 13 16 0 16 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 38 122 0 15 Sep 2019
Sparse and Imperceivable Adversarial Attacks Francesco Croce Matthias Hein AAML 39 199 0 11 Sep 2019
When Explainability Meets Adversarial Learning: Detecting Adversarial Examples using SHAP Signatures Gil Fidel Ron Bitton A. Shabtai FAtt GAN 21 119 0 08 Sep 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 11 58 0 25 Aug 2019
Denoising and Verification Cross-Layer Ensemble Against Black-box Adversarial Attacks Ka-Ho Chow Wenqi Wei Yanzhao Wu Ling Liu AAML 25 15 0 21 Aug 2019
Protecting Neural Networks with Hierarchical Random Switching: Towards Better Robustness-Accuracy Trade-off for Stochastic Defenses Tianlin Li Siyue Wang Pin-Yu Chen Yanzhi Wang Brian Kulis Xue Lin S. Chin AAML 16 42 0 20 Aug 2019
Nesterov Accelerated Gradient and Scale Invariance for Adversarial Attacks Jiadong Lin Chuanbiao Song Kun He Liwei Wang J. Hopcroft AAML 38 555 0 17 Aug 2019
Adversarial shape perturbations on 3D point clouds Daniel Liu Ronald Yu Hao Su 3DPC 33 12 0 16 Aug 2019
DAPAS : Denoising Autoencoder to Prevent Adversarial attack in Semantic Segmentation Seungju Cho Tae Joon Jun Byungsoo Oh Daeyoung Kim 27 31 0 14 Aug 2019
Once a MAN: Towards Multi-Target Attack via Learning Multi-Target Adversarial Network Once Jiangfan Han Xiaoyi Dong Ruimao Zhang Dongdong Chen Weiming Zhang Nenghai Yu Ping Luo Xiaogang Wang AAML 24 28 0 14 Aug 2019
Universal Adversarial Audio Perturbations Sajjad Abdoli L. G. Hafemann Jérôme Rony Ismail Ben Ayed P. Cardinal Alessandro Lameiras Koerich AAML 25 51 0 08 Aug 2019
Improved Adversarial Robustness by Reducing Open Space Risk via Tent Activations Andras Rozsa Terrance E. Boult AAML 30 18 0 07 Aug 2019
BlurNet: Defense by Filtering the Feature Maps Ravi Raju Mikko H. Lipasti AAML 42 15 0 06 Aug 2019
Imperio: Robust Over-the-Air Adversarial Examples for Automatic Speech Recognition Systems Lea Schonherr Thorsten Eisenhofer Steffen Zeiler Thorsten Holz D. Kolossa AAML 54 63 0 05 Aug 2019
NeuroMask: Explaining Predictions of Deep Neural Networks through Mask Learning M. Alzantot Amy Widdicombe S. Julier Mani B. Srivastava AAML FAtt 20 3 0 05 Aug 2019
Impact of Adversarial Examples on Deep Learning Models for Biomedical Image Segmentation Utku Ozbulak Arnout Van Messem W. D. Neve MedIm AAML 20 60 0 30 Jul 2019
On the Design of Black-box Adversarial Examples by Leveraging Gradient-free Optimization and Operator Splitting Method Pu Zhao Sijia Liu Pin-Yu Chen Nghia Hoang Kaidi Xu B. Kailkhura Xue Lin AAML 27 54 0 26 Jul 2019
Defense Against Adversarial Attacks Using Feature Scattering-based Adversarial Training Haichao Zhang Jianyu Wang AAML 23 230 0 24 Jul 2019
Towards Adversarially Robust Object Detection Haichao Zhang Jianyu Wang AAML ObjD 23 130 0 24 Jul 2019
Characterizing Attacks on Deep Reinforcement Learning Xinlei Pan Chaowei Xiao Warren He Shuang Yang Jian Peng ... Jinfeng Yi Zijiang Yang Mingyan D. Liu Bo-wen Li D. Song AAML 14 69 0 21 Jul 2019
Structure-Invariant Testing for Machine Translation Pinjia He Clara Meister Z. Su 27 104 0 19 Jul 2019
Constrained Concealment Attacks against Reconstruction-based Anomaly Detectors in Industrial Control Systems Alessandro Erba Riccardo Taormina S. Galelli Marcello Pogliani Michele Carminati S. Zanero Nils Ole Tippenhauer AAML 28 22 0 17 Jul 2019
A Novel User Representation Paradigm for Making Personalized Candidate Retrieval Zheng Liu Yu Xing Jianxun Lian Defu Lian Ziyao Li Xing Xie 32 3 0 15 Jul 2019
Measuring the Transferability of Adversarial Examples D. Petrov Timothy M. Hospedales SILM AAML 20 23 0 14 Jul 2019
Metamorphic Testing of a Deep Learning based Forecaster Anurag Dwarakanath Manish Ahuja Sanjay Podder Silja Vinu Arijit Naskar M. Koushik AI4TS 16 9 0 13 Jul 2019
Unsupervised Adversarial Attacks on Deep Feature-based Retrieval with GAN Guoping Zhao Mingyu Zhang Jiajun Liu Ji-Rong Wen AAML GAN 22 25 0 12 Jul 2019
PhysGAN: Generating Physical-World-Resilient Adversarial Examples for Autonomous Driving Zelun Kong Junfeng Guo Ang Li Cong Liu AAML 36 126 0 09 Jul 2019
Detecting and Diagnosing Adversarial Images with Class-Conditional Capsule Reconstructions Yao Qin Nicholas Frosst S. Sabour Colin Raffel G. Cottrell Geoffrey E. Hinton GAN AAML 19 71 0 05 Jul 2019
Minimally distorted Adversarial Examples with a Fast Adaptive Boundary Attack Francesco Croce Matthias Hein AAML 43 474 0 03 Jul 2019
Accurate, reliable and fast robustness evaluation Wieland Brendel Jonas Rauber Matthias Kümmerer Ivan Ustyuzhaninov Matthias Bethge AAML OOD 13 113 0 01 Jul 2019
Robust and Resource Efficient Identification of Two Hidden Layer Neural Networks M. Fornasier T. Klock Michael Rauchensteiner 24 18 0 30 Jun 2019
Robustness Guarantees for Deep Neural Networks on Videos Min Wu Marta Z. Kwiatkowska AAML 19 22 0 28 Jun 2019
Evolving Robust Neural Architectures to Defend from Adversarial Attacks Shashank Kotyan Danilo Vasconcellos Vargas OOD AAML 24 36 0 27 Jun 2019
Adversarial Robustness via Label-Smoothing Morgane Goibert Elvis Dohmatob AAML 10 18 0 27 Jun 2019
Invariance-inducing regularization using worst-case transformations suffices to boost accuracy and spatial robustness Fanny Yang Zuowen Wang C. Heinze-Deml 28 42 0 26 Jun 2019
Defending Adversarial Attacks by Correcting logits Yifeng Li Lingxi Xie Ya Zhang Rui Zhang Yanfeng Wang Qi Tian AAML 29 5 0 26 Jun 2019
Universal Litmus Patterns: Revealing Backdoor Attacks in CNNs Soheil Kolouri Aniruddha Saha Hamed Pirsiavash Heiko Hoffmann AAML 27 231 0 26 Jun 2019
Quantitative Verification of Neural Networks And its Security Applications Teodora Baluta Shiqi Shen Shweta Shinde Kuldeep S. Meel P. Saxena AAML 21 104 0 25 Jun 2019