adversarial machine learning

BagFlip: A Certified Defense Against Data Poisoning NeurIPS 2022 Being Friends Instead of Adversaries: Deep Networks Learn from Data Simplified by Other Networks AAAI 2022 Marksman Backdoor: Backdoor Attacks with Arbitrary Target Class NeurIPS 2022 Neurotoxin: Durable Backdoors in Federated Learning ICML 2022 Accumulative Poisoning Attacks on Real-time Data NeurIPS 2021 Defending SVMs against poisoning attacks: the hardness and DBSCAN approach UAI 2021 Markpainting: Adversarial Machine Learning meets Inpainting ICML 2021 Rethinking the Backdoor Attacks' Triggers: A Frequency Perspective ICCV 2021 SPECTRE: defending against backdoor attacks using robust statistics ICML 2021 Topological Detection of Trojaned Neural Networks NeurIPS 2021 WaNet - Imperceptible Warping-based Backdoor Attack ICLR 2021 Attack of the Tails: Yes, You Really Can Backdoor Federated Learning NeurIPS 2020 Protecting Geolocation Privacy of Photo Collections AAAI 2020 TBT: Targeted Neural Network Attack With Bit Trojan CVPR 2020 Universal Litmus Patterns: Revealing Backdoor Attacks in CNNs CVPR 2020 Adversarial Machine Learning with Double Oracle IJCAI 2019 Inaudible Voice Commands: The Long-Range Attack and Defense NSDI 2018 The Hidden Vulnerability of Distributed Learning in Byzantium ICML 2018 Is Feature Selection Secure against Training Data Poisoning? ICML 2015