v1v2v3v4 (latest)

Procedural Noise Adversarial Examples for Black-Box Attacks on Deep Convolutional Networks

30 September 2018

Papers citing "Procedural Noise Adversarial Examples for Black-Box Attacks on Deep Convolutional Networks"

28 / 28 papers shown

Title
Adversarial Examples in Environment Perception for Automated Driving (Review) Jun Yan Huilin Yin AAML 240 1 0 11 Apr 2025
"Real Attackers Don't Compute Gradients": Bridging the Gap Between Adversarial ML Research and Practice Giovanni Apruzzese Hyrum S. Anderson Savino Dambra D. Freeman Fabio Pierazzi Kevin A. Roundy AAML 244 105 0 29 Dec 2022
UniCR: Universally Approximated Certified Robustness via Randomized SmoothingEuropean Conference on Computer Vision (ECCV), 2022 Hanbin Hong Binghui Wang Yuan Hong AAML 153 15 0 05 Jul 2022
Analysis and Extensions of Adversarial Training for Video Classification K. A. Kinfu René Vidal AAML 203 14 0 16 Jun 2022
Smart App Attack: Hacking Deep Learning Models in Android AppsIEEE Transactions on Information Forensics and Security (IEEE TIFS), 2022 Yujin Huang Chunyang Chen FedML AAML 154 23 0 23 Apr 2022
Jacobian Ensembles Improve Robustness Trade-offs to Adversarial AttacksInternational Conference on Artificial Neural Networks (ICANN), 2022 Kenneth T. Co David Martínez-Rego Zhongyuan Hau Emil C. Lupu AAML 113 5 0 19 Apr 2022
NetSentry: A Deep Learning Approach to Detecting Incipient Large-scale Network AttacksComputer Communications (Comput. Commun.), 2022 Haoyu Liu P. Patras AAML 158 18 0 20 Feb 2022
Perlin Noise Improve Adversarial Robustness C. Tang Kun Zhang Chunfang Xing Yong Ding Zengmin Xu AAML 106 4 0 26 Dec 2021
On Procedural Adversarial Noise Attack And Defense Jun Yan Xiaoyang Deng Huilin Yin Wancheng Ge AAML 168 2 0 10 Aug 2021
Universal 3-Dimensional Perturbations for Black-Box Attacks on Video Recognition SystemsIEEE Symposium on Security and Privacy (IEEE S&P), 2021 Shangyu Xie Zheng Chen Yu Kong Yuan Hong AAML 206 29 0 09 Jul 2021
Real-time Adversarial Perturbations against Deep Reinforcement Learning Policies: Attacks and Defenses Buse G. A. Tekgul Shelly Wang Samuel Marchal Nadarajah Asokan AAML OffRL 242 10 0 16 Jun 2021
BO-DBA: Query-Efficient Decision-Based Adversarial Attacks via Bayesian Optimization Zhuosheng Zhang Shucheng Yu AAML 135 2 0 04 Jun 2021
Real-time Detection of Practical Universal Adversarial Perturbations Kenneth T. Co Luis Muñoz-González Leslie Kanthan Emil C. Lupu AAML 180 8 0 16 May 2021
Jacobian Regularization for Mitigating Universal Adversarial PerturbationsInternational Conference on Artificial Neural Networks (ICANN), 2021 Kenneth T. Co David Martínez-Rego Emil C. Lupu AAML 197 9 0 21 Apr 2021
Adversarial Examples Detection beyond Image SpaceIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2021 Kejiang Chen YueFeng Chen Hang Zhou Chuan Qin Xiaofeng Mao Weiming Zhang Nenghai Yu AAML 103 13 0 23 Feb 2021
Realizable Universal Adversarial Perturbations for Malware Raphael Labaca-Castro Luis Muñoz-González Feargus Pendlebury Gabi Dreo Rodosek Fabio Pierazzi Lorenzo Cavallaro AAML 156 8 0 12 Feb 2021
Object Removal Attacks on LiDAR-based 3D Object Detectors Zhongyuan Hau Kenneth T. Co Soteris Demetriou Emil C. Lupu 3DPC AAML 91 48 0 07 Feb 2021
Custom Object Detection via Multi-Camera Self-Supervised Learning Yan Lu Yuanchao Shu 114 3 0 05 Feb 2021
Dependency Decomposition and a Reject Option for Explainable Models Jan Kronenberger Anselm Haselhoff FAtt AAML 223 8 0 11 Dec 2020
Robustness and Transferability of Universal Attacks on Compressed Models Alberto G. Matachana Kenneth T. Co Luis Muñoz-González David Martínez Emil C. Lupu AAML 155 11 0 10 Dec 2020
Deep Neural Mobile Networking Chaoyun Zhang 169 2 0 23 Oct 2020
Vulnerability of deep neural networks for detecting COVID-19 cases from chest X-ray images to universal adversarial attacks Hokuto Hirano K. Koga Kazuhiro Takemoto AAML 204 49 0 22 May 2020
Blind Backdoors in Deep Learning Models Eugene Bagdasaryan Vitaly Shmatikov AAML FedML SILM 392 350 0 08 May 2020
Fundamental Tradeoffs between Invariance and Sensitivity to Adversarial PerturbationsInternational Conference on Machine Learning (ICML), 2020 Florian Tramèr Jens Behrmann Nicholas Carlini Nicolas Papernot J. Jacobsen AAML SILM 150 97 0 11 Feb 2020
Universal Adversarial Robustness of Texture and Shape-Biased ModelsInternational Conference on Information Photonics (ICIP), 2019 Kenneth T. Co Luis Muñoz-González Leslie Kanthan Ben Glocker Emil C. Lupu 282 18 0 23 Nov 2019
Black-box Adversarial Attacks with Bayesian Optimization Satya Narayan Shukla Anit Kumar Sahu Devin Willmott J. Zico Kolter AAML MLAU 124 33 0 30 Sep 2019
Sensitivity of Deep Convolutional Networks to Gabor NoiseInternational Conference on Machine Learning (ICML), 2019 Kenneth T. Co Luis Muñoz-González Emil C. Lupu AAML 130 6 0 08 Jun 2019
Taking Care of The Discretization Problem: A Comprehensive Study of the Discretization Problem and A Black-Box Adversarial Attack in Discrete Integer DomainIEEE Transactions on Dependable and Secure Computing (TDSC), 2019 Lei Bu Yuchao Duan Fu Song Zhe Zhao AAML 321 21 0 19 May 2019