adversarial attack

Detection and Defense of Topological Adversarial Attacks on Graphs AISTATS 2021 Disrupting Deep Uncertainty Estimation Without Harming Accuracy NeurIPS 2021 Don’t Search for a Search Method — Simple Heuristics Suffice for Adversarial Text Attacks EMNLP 2021 Drawing Robust Scratch Tickets: Subnetworks with Inborn Robustness Are Found within Randomly Initialized Networks NeurIPS 2021 DSRNA: Differentiable Search of Robust Neural Architectures CVPR 2021 EDGE: Explaining Deep Reinforcement Learning Policies NeurIPS 2021 Efficient Certification of Spatial Robustness AAAI 2021 Elastic Graph Neural Networks ICML 2021 Enabling Fast and Universal Audio Adversarial Attack Using Generative Model AAAI 2021 Enhanced Regularizers for Attributional Robustness AAAI 2021 Enhancing the Transferability of Adversarial Attacks Through Variance Tuning CVPR 2021 Evaluating Deception Detection Model Robustness To Linguistic Variation NAACL 2021 Exacerbating Algorithmic Bias through Fairness Attacks AAAI 2021 Excess Capacity and Backdoor Poisoning NeurIPS 2021 Exploring Adversarial Fake Images on Face Manifold CVPR 2021 Expressive 1-Lipschitz Neural Networks for Robust Multiple Graph Learning against Adversarial Attacks ICML 2021 FaceSec: A Fine-Grained Robustness Evaluation Framework for Face Recognition Systems CVPR 2021 Fast Minimum-norm Adversarial Attacks through Adaptive Norm Constraints NeurIPS 2021 Fast Training of Provably Robust Neural Networks by SingleProp AAAI 2021 Fault-Tolerant Federated Reinforcement Learning with Theoretical Guarantee NeurIPS 2021 Feature Importance-Aware Transferable Adversarial Attacks ICCV 2021 Feature Space Targeted Attacks by Statistic Alignment IJCAI 2021 Finding Optimal Tangent Points for Reducing Distortions of Hard-label Attacks NeurIPS 2021 Fine-tuning Is Not Enough: A Simple yet Effective Watermark Removal Attack for DNN Models IJCAI 2021 Fooling LiDAR Perception via Adversarial Trajectory Perturbation ICCV 2021