poisoning attack

RFLPA: A Robust Federated Learning Framework against Poisoning Attacks with Secure Aggregation NeurIPS 2024 Robust and Faster Zeroth-Order Minimax Optimization: Complexity and Applications NeurIPS 2024 Robust Nonparametric Regression under Poisoning Attack AAAI 2024 Semantic Shield: Defending Vision-Language Models Against Backdooring and Poisoning via Fine-grained Knowledge Alignment CVPR 2024 SleeperNets: Universal Backdoor Poisoning Attacks Against Reinforcement Learning Agents NeurIPS 2024 Tolerating Outliers: Gradient-Based Penalties for Byzantine Robustness and Inclusion IJCAI 2024 Towards the Robustness of Differentially Private Federated Learning AAAI 2024 Understanding and Improving Adversarial Collaborative Filtering for Robust Recommendation NeurIPS 2024 Universal Vulnerabilities in Large Language Models: Backdoor Attacks for In-context Learning EMNLP 2024 Certified Robust Neural Networks: Generalization and Corruption Resistance ICML 2023 Defending against Insertion-based Textual Backdoor Attacks via Attribution ACL 2023 Denial-of-Service or Fine-Grained Control: Towards Flexible Model Poisoning Attacks on Federated Learning IJCAI 2023 Enhancing the Antidote: Improved Pointwise Certifications against Poisoning Attacks AAAI 2023 Exploring Model Dynamics for Accumulative Poisoning Discovery ICML 2023 Few-shot Backdoor Attacks via Neural Tangent Kernels ICLR 2023 Graph Contrastive Backdoor Attacks ICML 2023 Large Language Models Are Better Adversaries: Exploring Generative Clean-Label Backdoor Attacks Against Text Classifiers EMNLP 2023 Mitigating Backdoor Poisoning Attacks through the Lens of Spurious Correlation EMNLP 2023 Poisoning-Based Backdoor Attacks in Computer Vision AAAI 2023 Poisoning Generative Replay in Continual Learning to Promote Forgetting ICML 2023 Poisoning the Well: Can We Simultaneously Attack a Group of Learning Agents? IJCAI 2023 Preventing Attacks in Interbank Credit Rating with Selective-aware Graph Neural Network IJCAI 2023 Revisiting Graph Adversarial Attack and Defense From a Data Distribution Perspective ICLR 2023 The Perils of Learning From Unlabeled Data: Backdoor Attacks on Semi-supervised Learning ICCV 2023 Towards Attack-tolerant Federated Learning via Critical Parameter Analysis ICCV 2023