Transferability in Machine Learning: from Phenomena to Black-Box Attacks using Adversarial Samples

24 May 2016

Papers citing "Transferability in Machine Learning: from Phenomena to Black-Box Attacks using Adversarial Samples"

22 / 22 papers shown

Title
Towards more transferable adversarial attack in black-box manner Chun Tong Lei Zhongliang Guo Hon Chung Lee Minh Quoc Duong Chun Pong Lau DiffM AAML 126 0 0 23 May 2025
Towards Model Resistant to Transferable Adversarial Examples via Trigger Activation Yi Yu Song Xia Xun Lin Chenqi Kong Wenhan Yang Shijian Lu Yap-Peng Tan Alex C. Kot AAML SILM 347 0 0 20 Apr 2025
From Visual Explanations to Counterfactual Explanations with Latent Diffusion Tung Luu Nam Le Duc Le Bac Le DiffM AAML FAtt 93 0 0 12 Apr 2025
AMUN: Adversarial Machine UNlearning A. Boroojeny Hari Sundaram Varun Chandrasekaran MU AAML 57 0 0 02 Mar 2025
Enabling AutoML for Zero-Touch Network Security: Use-Case Driven Analysis Li Yang Mirna El Rajab Abdallah Shami Sami Muhaidat 101 7 0 28 Feb 2025
Cross-Modal Transferable Image-to-Video Attack on Video Quality Metrics Georgii Gotin E. Shumitskaya Anastasia Antsiferova D. Vatolin AAML 59 0 0 14 Jan 2025
Adversarial Training Can Provably Improve Robustness: Theoretical Analysis of Feature Learning Process Under Structured Data Binghui Li Yuanzhi Li OOD 46 2 0 11 Oct 2024
Understanding Model Ensemble in Transferable Adversarial Attack Wei Yao Zeliang Zhang Huayi Tang Yong Liu 48 3 0 09 Oct 2024
Partner in Crime: Boosting Targeted Poisoning Attacks against Federated Learning Shihua Sun Shridatt Sugrim Angelos Stavrou Haining Wang AAML 84 1 0 13 Jul 2024
Bidirectional Consistency Models Liangchen Li Jiajun He DiffM 74 12 0 26 Mar 2024
Towards Adversarially Robust Dataset Distillation by Curvature Regularization Eric Xue Yijiang Li Haoyang Liu Yifan Shen Haohan Wang Haohan Wang DD 79 8 0 15 Mar 2024
Accelerated Smoothing: A Scalable Approach to Randomized Smoothing Devansh Bhardwaj Kshitiz Kaushik Sarthak Gupta AAML 46 0 0 12 Feb 2024
Beyond Boundaries: A Comprehensive Survey of Transferable Attacks on AI Systems Guangjing Wang Ce Zhou Yuanda Wang Bocheng Chen Hanqing Guo Qiben Yan AAML SILM 85 3 0 20 Nov 2023
HoSNN: Adversarially-Robust Homeostatic Spiking Neural Networks with Adaptive Firing Thresholds Hejia Geng Peng Li AAML 48 3 0 20 Aug 2023
Nash Equilibria, Regularization and Computation in Optimal Transport-Based Distributionally Robust Optimization Soroosh Shafieezadeh-Abadeh Liviu Aolaritei Florian Dorfler Daniel Kuhn 86 21 0 07 Mar 2023
Practical No-box Adversarial Attacks with Training-free Hybrid Image Transformation Qilong Zhang Chaoning Zhang Chaoning Zhang Chaoqun Li Xuanhan Wang Jingkuan Song Lianli Gao AAML 51 21 0 09 Mar 2022
Adversarial Examples on Object Recognition: A Comprehensive Survey A. Serban E. Poll Joost Visser AAML 53 73 0 07 Aug 2020
Towards Robust and Stable Deep Learning Algorithms for Forward Backward Stochastic Differential Equations Batuhan Güler Alexis Laignelet P. Parpas OOD 67 16 0 25 Oct 2019
Generating Natural Adversarial Examples Zhengli Zhao Dheeru Dua Sameer Singh GAN AAML 102 599 0 31 Oct 2017
Evasion Attacks against Machine Learning at Test Time Battista Biggio Igino Corona Davide Maiorca B. Nelson Nedim Srndic Pavel Laskov Giorgio Giacinto Fabio Roli AAML 74 2,140 0 21 Aug 2017
Simple Black-Box Adversarial Perturbations for Deep Networks Nina Narodytska S. Kasiviswanathan AAML 41 237 0 19 Dec 2016
Poisoning Attacks against Support Vector Machines Battista Biggio B. Nelson Pavel Laskov AAML 50 1,580 0 27 Jun 2012